23-08 amend 12 third repub.pdf

AMENDMENT 12 TO BAA FA8750-23-S-7008

The purpose of this modification is to republish the original announcement, incorporating any previous amendments, pursuant to FAR 35.016(c).

This republishing also includes the following changes:

1. Part I, Overview Information:

a. Updates the Federal Agency Name;

2. Part II, Full Text Announcement:

a. Section V.3, updates the Simplified Acquisition Threshold to $350,000;

b. Section V.4, updates the certified cost and pricing data threshold to $10M for large businesses;

c. Section VI.1, updates the proposal formatting language;

d. Section VI.3, updates the debriefing language;

e. Section VI.5.b.3, updates the DFARS clause;

f. Section VI.5.c, updates the DFARS clause;

g. Section VI.7, updates the provisions;

h. Section VI.9; updates the DFARS reference;

i. Section VII: updates the OMBUDSMAN language.

No other changes have been made.

NAICS CODE: 541715

FEDERAL AGENCY NAME: Department of the Air Force, Air Force Materiel Command, AFRL

- Rome Research Site, AFRL/Information & Spectrum Warfare Directorate, 26 Electronic Parkway, Rome, NY, 13441-4514

BAA ANNOUNCEMENT TYPE: Modification

BROAD AGENCY ANNOUNCEMENT (BAA)

TITLE: Adaptive Fusion, Analysis & Reasoning of multi-source data (AFAR)

BAA NUMBER: FA8750-23-S-7008

PART I – OVERVIEW INFORMATION

This announcement is for an Open, 2 Step BAA which is open and effective until 29 Aug 2028. Only white papers will be accepted as initial submissions; formal proposals will be accepted by invitation only. While white papers will be considered if received prior to 11:59PM Eastern Standard Time (EST), the following submission dates are suggested to best align with projected funding:

FY24 by 12 Sep 2023 (Please note: For only FY24, AFRL is seeking whitepapers for just the following Focus Areas: A - Adaptive Knowledge and Information for Target Analysis and B - Enhancing Moving Target Engagement at Scale (EMoTES)) FY25 by 15 Jul 2024 FY26 Focus Area B3 by 28 APR 2025 FY26 by 15 Jul 2025 FY27 by 15 Jul 2026 FY28 by 15 Jul 2027

Offerors should monitor the Contract Opportunities on the SAM website at https://SAM.gov in the event this announcement is amended.

CONCISE SUMMARY OF TECHNOLOGY REQUIREMENT: The Air Force Research Laboratory, Information Directorate is seeking innovative approaches for the fusion, analysis and reasoning of multi-source data to advance their analytical operations in support of their Command, Control, Communications, Computers and Intelligence (C4I) and Cyber Science mission. This announcement is comprised of four research areas: (A) Adaptive Knowledge and Information for Target Analysis (AKITA), (B) Enhancing Moving Target Engagement at Scale (EMoTES) and (C) Publicly Available Information (PAI) Ensemble Fusion (PEF), and (D) Agentic AI Workflows for Dynamic Operational Contexts (AWARD) where each has research areas that taken together comprise the focus of AFAR research and development.

BAA ESTIMATED FUNDING: Total funding for this BAA is approximately $99.9M. Individual awards will not normally exceed 36 months with dollar amounts normally ranging from $500K to $3M.

There is also the potential to make awards up to any dollar value as long as the value does not exceed the available BAA ceiling amount. Any anticipated funding listed reflects estimated program funding only. This estimate is not a promise of funding. Funding is uncertain and is subject to change. Changes in availability may occur as a result of the exercise of Government discretion.

ANTICIPATED INDIVIDUAL AWARDS: Multiple Awards are anticipated. However, the Air Force reserves the right to award zero, one, or more Procurement Contracts or Assistance Instruments for all, some, or none of the solicited effort based on the offeror’s ability to perform desired work and funding fluctuations.

TYPE OF INSTRUMENTS THAT MAY BE AWARDED: FAR based Procurement contracts, CFR based grants and cooperative agreements or other transactions (OT) under 10 USC 4021, 10 USC 4022 ( previously 10 USC 4002, 2371, 10 USC 4003, 2371b) depending upon the nature of the work proposed. 10 USC 4023 also allows for FAR based contracts, OTs for research, OTs for Prototype, and assistance instruments.

In the event that an Other Transaction for Prototype agreement is awarded as a result of this competitive BAA, and the prototype project is successfully completed, there is the potential for a prototype project to transition to award of a follow-on production contract or transaction. The Other Transaction for Prototype agreement itself will also contain a similar notice of a potential follow-on production contract or agreement.

REGARDING ASSISTANCE INSTRUMENTS: Gold Standard Science (GSS): IAW EO 14303;

GSS is science conducted in a manner that is:

a. reproducible;

https://sam.gov/

b. transparent;

c. communicative of error and uncertainty;

d. collaborative and interdisciplinary;

e. skeptical of its findings and assumptions;

f. structured for falsifiability of hypotheses;

g. subject to unbiased peer review;

h. accepting negative results as positive outcomes; and

i. without conflicts of interest.”

With regards to GSS, white papers/proposals shall:

1. include clear benchmarks for measuring success and progress towards relevant goals and a commitment to achieving GSS;

2. identify areas of demonstrating success in implementing GSS; and

3. include a commitment to complying with administration policies, procedures, and guidance respecting GSS. By responding to this BAA you explicitly agree to the following statement:

• Our institution understoods the definition of Gold Standard Science as outlined above.

• Our institution and all personnel involved in the proposed project will adhere to all administration policies, procedures, and guidance respecting Gold Standard Science in the execution of this project if funded.

AGENCY CONTACT INFORMATION: All white paper submissions and any questions of a technical nature shall be directed to the cognizant Technical Point of Contact (TPOC) as specified below (unless otherwise specified in the technical area):

BAA PROGRAM MANAGER (Primary):

John Spina

AFRL/RIEA

525 Brooks Rd Rome, NY 13441-4505 Telephone: (315)330-4032 Email: john.spina@us.af.mil

BAA PROGRAM MANAGER (Secondary):

Rosanne Pelli

AFRL/RIEA

525 Brooks Rd Rome, NY 13441-4505 Telephone: (315)330-4734 Email: rosanne.pelli@us.af.mil

Questions of a contractual/business nature shall be directed to the cognizant contracting officer, as specified below (email requests are preferred):

Amber Buckley Email: Amber.Buckley@us.af.mil

Emails must reference the solicitation BAA number (FA8750-23-S-7008) and title of the acquisition.

mailto:john.spina@us.af.mil mailto:rosanne.pelli@us.af.mil mailto:Amber.Buckley@us.af.mil

Pre-Proposal Communication between Prospective Offerors and Government Representatives:

Dialogue between prospective offerors and Government representatives is encouraged. Technical and contracting questions can be resolved in writing or through open discussions. Discussions with any of the points of contact shall not constitute a commitment by the Government to subsequently fund or award any proposed effort. Only Contracting Officers are legally authorized to commit the Government.

Offerors are cautioned that evaluation ratings may be lowered and/or proposal rejected if proposal preparation (Proposal format, content, etc.) and/or submittal instructions are not followed.

PART II – FULL TEXT ANNOUNCEMENT

BROAD AGENCY ANNOUNCEMENT (BAA)

TITLE: Adaptive Fusion, Analysis & Reasoning of multi-source data (AFAR)

BAA NUMBER: BAA FA8750-23-S-7008

Assistance Listing Number: 12.800, 12.910

Federal Acquisition Supply Chain Security Act (FASCSA) Orders: Depending on the date of issuance of this solicitation, FASCSA order(s) may be applicable. Therefore, the Offeror shall search for the phrase “FASCSA order” in the System for Award Management (SAM) (https://www.sam.gov) for any covered article, or any products or services produced or provided by a source, if there is an applicable Federal Acquisition Supply Chain Security Act Orders prohibition. This requirement only applies to FAR based awards.

I. TECHNOLOGY REQUIREMENTS:

The Air Force Research Laboratory/Information Directorate (AFRL/RI), Information Fusion Branch, is soliciting white papers under this announcement for unique and innovative technologies to explore and develop AFAR capabilities including but not limited to, analytics, analytical tools, algorithm developments, projects, and experiments that will provide the Air Force the means to better conduct analytical operations in support of their Command, Control, Communications, Computers and Intelligence (C4I) and Cyber Science mission. This announcement is comprised of four research areas:

(A) Adaptive Knowledge and Information for Target Analysis (AKITA), (B) Enhancing Moving Target Engagement at Scale (EMoTES), (C) Publicly Available Information (PAI) Ensemble Fusion (PEF), and (D) Agentic AI Workflows for Dynamic Operational Contexts (AWARD), where each has research areas that taken together comprise the focus of AFAR research and development.

BACKGROUND: Air Force analysts are inundated with large quantities of data that need to be cultivated and assessed throughout the peer fight challenge. Due to the quantity and diversity of AF Intelligence data, this analysis can be time consuming and costly, as it remains a manually intensive task for analysts. Fundamentally the analysis of data must produce higher levels of comprehension and understanding than presently exists. As data and information have increased in both quantity and complexity, the demands for greater analytical capabilities have also grown dramatically. According to the Next Generation ISR Dominance Flight Plan (2018 – 2028), the Air Force does not fully harness or integrate all potential information sources at its disposal, resulting in limited insights into adversary https://www.sam.gov/ intent, capability, and operational execution. The ability of decision makers to receive, process, and react to actionable intelligence is inhibited by the dispersion of information across platforms and networks. Further development is required to not just keep pace but to move beyond current performance levels, to overcome limitations in moving to new data types and domains, and to achieve new, more sophisticated capabilities.

One of the greatest technical challenges facing all decision support systems is the heterogeneous aspect of the data that is collected by millions of sensors and the different stovepipe architectures used to store this data. In order to perform useful analytics, a composite picture of the key entities, events, and locations need to be pieced together from the original disparate data sources. The ingesting, fusion and understanding of information from disparate data sources remains a difficult and unresolved problem.

AFRL is seeking novel research and development approaches to advancing the automation of comprehensive knowledge graph generation and enhancing moving target engagements at scale. This BAA also seeks the development of state-of-the-art technologies in data alignment for large-scale, disparate data sources and creating analytical models for estimating “tactical” phenomena that occur in publicly available information (PAI)/commercially available information (CAI).

Knowledge graphs provide a natural framework for aligning and reasoning over large amounts of heterogenous/multi-modal data for downstream decision making, and analysis tools are being developed to support this reasoning. However, these analysis tools assume that the knowledge graph already exists;

research is needed to automate the generation of a more comprehensive knowledge graph from multiple heterogeneous data sources to speed up the current targeting timeline.

Currently, tracking sensors are manually controlled by operators, and identifying high-value targets (HVTs) from amongst the tracked objects is done through ad-hoc multi-modal data fusion (via ELINT, EO/IR, track data). This manual process delays the find, fix, track, target, engage, and assess (F2T2EA) kill chain - where every second is vital in a near peer conflict. Automatically identifying and proposing a list of potential HVTs to a human-on-the-loop will enable the rapid re-tasking of tracking sensors for a faster kill chain. For the past thirty years, a common solution for dynamic decision-making has been “Multi-criteria decision-analysis” (MCDA). The availability of operational data is variable at a given time; information available may change from situation to situation, especially in a highly-contested environment. It is crucial that the system be able to adjust the weights of its attributes based on the availability of data so that a viable ranking of HVT’s could still be produced.

The idea of vastly dispersed data is particularly true in the burgeoning area of Publicly Available Information (PAI), which includes both open-source and commercially available data sources such as social media, mobile device data, road observation networks, commercial satellite information, and more. These datasets are highly heterogeneous, with complicated, overlapping information coverage areas, and varying degrees of accuracy and trustworthiness. As a whole this presents a number of challenges, including 1) how to characterize the veracity of information extracted from public data sets,

2) how to align indications of threat events across datasets to reduce redundant or conflicting information presented to analysts, and 3) how to fuse PAI-derived threat event indicators with information from traditional sensors.

OBJECTIVES: The four research areas within this AFAR BAA are (A) Adaptive Knowledge and Information for Target Analysis (AKITA), (B) Enhancing Moving Target Engagement at Scale (EMoTES) and (C) Publicly Available Information (PAI) Ensemble Fusion (PEF) and (D) Agentic AI Workflows for Dynamic Operational Contexts (AWARD) with each containing their respective key technical Focus Areas for development. Submissions/White Papers should clearly identify the AFAR research area or specify the individual Focus Area being addressed.

A. Adaptive Knowledge and Information for Target Analysis (AKITA): The AKITA research area will deliver automated fusion of heterogeneous multi-source intelligence data and store that information in a knowledge graph to alleviate the investigative burden of the targeting analytical process. The individual research areas of this focus area are (A1) Automated Intelligence Extraction and Mapping, (A2) Spatio-Temporal Grounding, and (A3) Systems Integration and Demonstration. These technologies are key enablers to significantly reduce the amount of time required to complete the research phase of Target Systems Analysis.

Submissions/White Papers for the AKITA Focus Area will only be accepted if they address the following Focus Area combinations: A1, A2 and A3, A1 and A2 or A3. Any other combination of focus areas is not permitted. Submissions to all four focus areas must ensure the budget and tasks are well delineated so that partial awards are possible. It is the government’s intent to provide an AF Intelligence dataset for use on AKITA, although offerors may utilize their own datasets as well if desired.

Focus Area A1 – Automated Intelligence Extraction and Mapping

This focus area will research and develop techniques for automated fusion of heterogeneous, multi-source Air Force Intelligence datasets and store the information in a knowledge graph. These data sets will consist of relatively static (i.e. MIDB) and dynamic (i.e. ChatSurfer) data, and the research should investigate methods for fusing both. It is suggested that offerors leverage existing techniques for extracting/structuring information from unstructured data where possible (i.e. image extraction, text extraction), as the primary focus of this area is automated data fusion. Fusion techniques should also accommodate mapping the data onto either a provided or customized ontology. The technical challenge this area aims to address may include (but are not limited to): ontology alignment and expansion, multi-source data extraction and fusion, knowledge graph generation, knowledge graph qualitative metrics, link prediction, and object/entity resolution.

Focus Area A2 – Spatio-Temporal Grounding

Targeting requires knowledge of where entities/objects are located at what time, as this can inform analytics such as discovering patterns of life and determining a course of action. This focus area will research and develop approaches for grounding real-world entities in space and time and updating that information as new information becomes available. The technical challenge this area aims to address may include (but are not limited to): multi-source event resolution, object attribute resolution, event linking, and ambiguous time/location references.

Focus Area A3 – Systems Integration and Demonstration

Technologies developed in A1 and A2 will need to be integrated into a system that enables analyst interaction and validation. Proper integration will result in a usable GUI for analysts to explore the knowledge graph and perform analyses. This focus area will integrate algorithms and capabilities from focus areas A1 and A2 into a platform for targeting analysis and may include R&D to support end-to-end functionality of the platform. This will enable demonstrations to customers and support evaluations of R&D capabilities. Adhering to best practices and standards to achieve design requirements and promote flexibility and interoperability is encouraged.

B. Enhancing Moving Target Engagement at Scale (EMoTES)

Key to the operational imperative for achieving Moving Target Engagement at Scale is improving our find/fix/track (F2T) capabilities for challenging and high-value targets (HVTs). Current approaches for target prioritization and sensor orchestration for target custody are ad-hoc and inadequate for expedited timelines that are expected in contested environments. EMoTES will investigate approaches to enhance the find portion of the kill chain via focus area (B1) Nomination of High-Value Targets and the fix/track portion via focus area (B2) Sensor Resource Management and Data Fusion. The ultimate goal of EMoTES is to enable the ability to feed targets found from B1 to B2 for improved custody.

Focus Area B1 – Nomination of High-Value Targets

There is inherent risk in deploying intelligence assets; In order to adapt to evolving scenarios under contested environments, rapid re-tasking of sensors to address emerging situations requires awareness and prioritization of high value targets (HVTs). AFRL/RI is seeking offerors to develop a Multi-int Adaptive Recommender System (MARS) that will address this operational need by investigating methods and techniques to reveal HVTs with a non-uniform, dynamic level of contextual data using a novel recommender system. MARS must leverage a fusion of heterogeneous data types including, but not limited to, Ground Moving Target Indicators (GMTI), Electronic Intelligence (ELINT), overhead imagery, Full-Motion Video (FMV), Synthetic Aperture Radar (SAR) imagery, and fused track data.

The Government may provide Government Furnished Information (GFI) for this technical area of MTI track data, convoy information, and SIGINT data for ground and maritime targets for related efforts.

In a contested environment, time spent on tasking is crucial; analysts often have a time budget to adapt to emerging situations. A key facet of B1 is minimizing the time between groups of recommendations provided to the analyst for re-tasking a platform. Another key consideration to be made is the level of data dynamism; given that the intelligence platforms could potentially be deployed in a highly contested environment, the data available to the recommender system will vary. The goal of B1 is to develop techniques for a man-on-the-loop recommender system to reveal HVTs based on analysts’ reaction and ranking feedback. The expected system developed will ingest a dynamic level of multi-int data and provide the user with a ranking of HVTs which the user can then re-rank to provide feedback to the system within a budgeted period of time. Metrics for evaluation should include, but are not limited to, precision, recall, convergence time and HVT recommendation speed.

See below for High Value Target definitions, which can also be found in: JP 3-60 Targeting; AFTTP 3-

2.3 Dynamic Targeting.

• Time-Sensitive Target (TST) (JP 3-60 Targeting) o A JFC-designated target or target type of such high importance to the accomplishment of the JFC’s mission and objectives, or one that presents such a significant strategic or operational threat to friendly forces or allies, that the JFC dedicates intelligence collection and attack assets away from other targets to F2T2EA such targets.

• High-Value Target (HVT) (AFTTP 3-2.3 Dynamic Targeting) o HVTs are assets the enemy commander maintains for the successful mission completion.

• JFC’s Critical Targets (CT) (AFTTP 3-2.3 Dynamic Targeting) o Are those targets designated by the JFC and identified as such in the JFC’s concept of operations. Normally, they represent a very small portion of the total number of targets due to the required investment of assets and potential disruption of planned execution. In most cases, JFC-CTs require an immediate response because they pose (or will soon pose) a direct danger to friendly forces or are lucrative targets of opportunity.

Focus Area B2 – Sensor Resource Management and Data Fusion

Driven by the current operational imperative for achieving Moving Target Indication and Tracking at Scale (air, sea surface and ground mobile targets), the Autonomous Sensing Grid Exploitation (ASX) objective is to develop and demonstrate autonomous multi-sensor resource management and data fusion approaches across a sensing grid (SG) for improved track custody and improved Situational Awareness (SA). Approaches must demonstrate the ability to outperform current ad-hoc approaches of multi-sensor tip & cue and common Area of Regard (AOR) strategies for sensor orchestration to feed a custody engine with motion detection data. This includes applied research necessary for critical missions to more effectively orchestrate, aggregate, and fuse data across sensors to provide better track custody necessary to find/fix/track (F2T) challenging targets.

AFRL has created a Systems Integration Laboratory (SIL) to support the installation, testing, analysis, and maturation of deliverables under this effort through our Automated Processing and Exploitation (APEX) Center. Utilizing the APEX Center M&S capabilities (and other Digital Engineering (DE) artifacts), various use cases will be utilized to provide metrics on track lifetime and sensor utilization/efficiency.

Due to the distributed nature of the sensors, various time scales, and heterogeneity of data exploitation, autonomously controlling a sensing grid is challenging. This program will pursue closed loop distributed sensor network management and data fusion. Use of available mature tracking capabilities to allow for local, distributed, & edge tracking (e.g., AFRL BRAT, ABMS CONSENSUS, others) performing sensor-to-track and track-to-track fusion is preferred. The Air Force is seeking additional work for sensor resource management within these research challenge areas:

• Research and develop approaches for resource management and logic to exploit decisional tracking information across platforms to map target states into decision variables for higher (task)-level platform and sensor actions that balances info needs against resource availability.

• Research and define best practices for scheduling policies via Reinforcement Learning (RL) for maximization of a reward function involving longer track lifetimes and track purity. The track/target state is used as feedback in the evaluation process to influence dynamic sensor modes, priorities, revisit, job, and dwell scheduling.

• Research and develop approaches methods to couple edge-processing capabilities with centralized management and fusion algorithms such that both global and local objectives can be supported. This distributed tracking approach will operate in an ABMS construct.

• Define and develop the Digital Engineering tools and artifacts necessary to support a systematic study to evaluate algorithm-specific metrics and the overall KPPs in the full context of an overall trade space.

Focus Area B3 – AFRL’s Processing and Exploitation Center Modernization

As noted in Focus Area B2, AFRL has a Systems Integration Lab (SIL) to support installation, testing, analysis, and maturation of digital artifacts through the Advanced Processing and Exploitation (APEX) Center. The APEX Center is used to perform analysis for multi-INT analysis tools, provide baseline tool development for major AFRL programs, and provide realistic operational systems, networks, databases, and software for integration efforts. AFRL is looking for:

• Development of automated capabilities of multi-INT data including (Open-Source Intelligence (OSINT), IMINT, GEOINT, Motion GEOINT, Communications Intelligence (COMINT), Human Intelligence (HUMINT), Signals Intelligence (SIGINT) data, Measurement and Signature Intelligence (MASINT), and Cyber Intelligence, Surveillance and Reconnaissance (ISR) data.

• Analysis of current data management capabilities to identify requirements to support the addition of other data types that would enable future analytical studies.

• Providing enhancements to data management capabilities.

• Implementing a Large Language Model to be used as a “chat bot” on the front end of a Web

Interface.

o Support for archival, retrieval, processing, reduction, formatting, characterization, and identification of appropriate and problem data sets.

o Interface to allows users fluid interaction with multiple structured and unstructured data sources.

• Evaluating and implementing visualization technology for continued analysis and demonstration of analytics and other technologies developed within the APEX Center.

Focus Area B4 – Space-based and tactical ISR Asset Orchestration

The next generation of ISR sensors will need to operate, navigate, and coordinate between other sensors autonomously. The integration of various sensors with new and existing command and control networks will be one of Space-Based Radars (SBR) biggest challenges. In a highly contested environment ISR assets will be limited in time on station and navigable routes. Stand-off assets such as traditional airborne sensors and emerging SBR have limited target sets and/or availability while tactical platforms such as new drones lack the ability for persistent coverage, both challenges lead to target information gaps in ISR tracking. AFRL is looking for research to solve the coordinated and distributed optimization of multi-entity inputs (traditional, space, tactical sensors) to solve a global objective of all sensors to maximize target state estimations in a contested maritime environment, with resiliency to target information gaps.

C. Publicly Available Information (PAI) Ensemble Fusion (PEF)

PEF will address key challenges in the analysis of publicly available information (PAI) (to also include commercially available information (CAI)) and multi-source fusion not only amongst PAI/CAI sources, but also in combination with traditional intelligence sources, empowering the analyst with high performance, high accuracy and easily adaptable tools for threat assessment, explanation, and anticipation surrounding entities of interest, groups and events. This research area will support the design and implementation of state-of-the-art technologies to achieve data alignment for large-scale, disparate data sources and create analytical models for estimating “tactical” phenomena that occur in PAI/CAI. The individual focus areas of this research area are (C1) Veracity Analysis and (C2) Multi- Modal Data Fusion.

PEF will develop a system that exploits the timely and fast-paced on-the-ground information inherent in PAI, while vetting these PAI sources and externally corroborating information with traditional intelligence sources, such as IMINT and MOVINT, to ensure accuracy of the information. The outcome of PEF will be increased threat forecasting precision, breadth of topics, and depth of evidential support.

Adhering to best practices and open standards that help the system attain these design requirements is encouraged.

Focus Area C1 – Veracity Analysis

The objective of this area is to establish and formalize methods for assessing the true information content of PAI data in order to optimally integrate sources with different levels of accuracy or veracity.

This will provide improved accuracy for PAI analytics, such as threat detection, over previous approaches by discounting or promoting sources through the identification of inconsistencies, biases, false information, and deliberate attempts at spreading misinformation. The expected outcome of this focus area is the increased usefulness and accessibility of PAI by analyzing source veracity for corroboration with external information. Veracity analysis methods will assess PAI from multiple sources and modalities and provide confidence scoring to detected threat events. In scope of this work will also be the detection, attribution, and characterization of deliberate attempts at misinformation to include deep fakes.

Focus Area C2 – Multi-Modal Fusion

Current analysis methods do not integrate all potential available information sources, more specifically PAI and traditional intelligence sources. This results in limited insights into an entity’s intent, capability, and activity. In addition, multi-modal fusion and threat detection methods for PAI are ad-hoc and focus on narrow domains of interest such as flood detection and unrest. PAI datasets are highly heterogeneous with complicated, overlapping coverage areas, with varying degrees of accuracy and trustworthiness.

Individual sources may be skewed or limited, but when taken as a whole and fused with traditional intelligence sources, can provide in depth characterization of threats. The technical challenge this area aims to address is the fusion of detected threat events with varying levels of confidence derived from multi-source, multi-modal PAI with traditional intelligence data sources. This differs from the traditional multi-INT fusion problem. While data from hard sensors will be highly accurate in time and space, PAI can lack specific information regarding location, time, etc. PAI sources that are of interest, but not limited to, are news, forums, social media, collateral telemetry data (CTD), commercial imagery, and Internet of Things (IoT) device information.

D. Agentic AI Workflows for Dynamic Operational Contexts (AWARD)

The AWARD research area will investigate the development and implementation of flexible, adaptable workflows powered by Agentic AI to enhance decision-making in complex and dynamic operational environments. The key research area within this focus area is: (D1) Multi-Agent Agentic AI Workflows to Accelerate Kill Chains. This technology is a key enabler for creating more responsive, resilient, and effective decision-making processes in challenging, data-rich operational settings.

Focus Area D1 – Multi-Agent Agentic AI Workflows to Accelerate Kill Chains

The character of warfare is undergoing a fundamental transformation, driven by the relentless advance of artificial intelligence. Large language Models (LLMs), now equipped with tools and memory, are making AI more powerful and accessible than ever before. Agentic AI workflows are helping humans process information more efficiently and have begun to outperform humans in reasoning tasks where humans are historically far superior. As agents learn to autonomously collaborate and reason together, we stand on the precipice of an intelligence revolution, where the sum is far greater than its parts.

Autonomous “multi-agent” agentic workflows offer a force multiplier, enabling the Air Force to manage, analyze, and act on data from a multitude of sources, including drones, with the speed, precision, and coordination required to prevail in future conflicts. AFRL is looking for research into multi-agent Agentic AI workflows within a modeling and simulation environment, providing Air Force operators with decision advantage in a future conflict where decision advantage is achieved through the optimal collaboration of human and machine intelligence, leveraging the unique strengths of each to inform, augment, and accelerate real-time decision-making.

IMPORTANT NOTES REGARDING:

1. FUNDAMENTAL RESEARCH. It is DoD policy that the publication of products of fundamental research will remain unrestricted to the maximum extent possible. National Security Decision Directive (NSDD) 189 defines fundamental research as follows:

‘Fundamental research’ means basic and applied research in science and engineering, the results of which ordinarily are published and shared broadly within the scientific community, as distinguished from proprietary research and from industrial development, design, production, and product utilization, the results of which ordinarily are restricted for proprietary or national security reasons.

As of the date of publication of this BAA, the Government cannot identify whether work proposed under this BAA may be considered fundamental research and may award both fundamental and non-fundamental research. Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to select award instrument type and to negotiate all instrument terms and conditions with selectees. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate.

For certain research projects, it may be possible that although the research being performed by the awardee is restricted research, a sub-awardee may be conducting fundamental research. In those cases, it is the awardee’s responsibility to explain in their proposal why its sub-awardee’s effort is fundamental research.

2. CLOUD COMPUTING. In accordance with DFARS Clause 252.239-7010, if the development proposed requires storage of Government, or Government-related data on the cloud, offerors need to ensure that the cloud service provider proposed has been granted Provisional Authorization by the Defense Information Systems Agency (DISA) at the level appropriate to the requirement.

II. AWARD INFORMATION:

1. FUNDING: Total funding for this BAA is approximately $99.9M. The anticipated funding to be obligated under this BAA is broken out by fiscal year as follows:

FY24 - $3.65M

FY25 - $5.30M

FY26 - $15.95M

FY27 - $29.50M

FY28 - $45.50M

a. Individual awards will not normally exceed 36 months with dollar values normally ranging from $100K to $3M. There is also the potential to make awards up to any dollar value as long as the value does not exceed the available BAA ceiling amount.

b. The Government reserves the right to select all, part, or none of the proposals received, subject to the availability of funds. All potential Offerors should be aware that due to unanticipated budget fluctuations, funding in any or all areas may change with little or no notice.

2. FORM. Awards of efforts as a result of this announcement will be in the form of contracts, grants, cooperative agreements depending upon the nature of the work proposed.

3. BAA TYPE: This is a two-step open broad agency announcement. This announcement constitutes the only solicitation.

As STEP ONE – The Government is only soliciting white papers at this time. DO NOT SUBMIT A FORMAL PROPOSAL. Those white papers found to be consistent with the intent of this BAA may be invited to submit a technical and cost proposal. See Section VI of this announcement for further details regarding the proposal.

III. ELIGIBILITY INFORMATION:

1. ELIGIBILITY: All qualified offerors who meet the requirements of this BAA may apply.

2. FOREIGN PARTICIPATION/ACCESS:

a. This BAA is closed to foreign participation. This includes both foreign ownership and foreign nationals as employees or subcontractors.

b. Exceptions.

i. Fundamental Research. If the work to be performed is unclassified, fundamental research, this must be clearly identified in the white paper and/or proposal. See Part II, Section I for more details regarding Fundamental Research. Offerors should still identify any performance by foreign nationals at any level (prime contractor or subcontractor) in their proposals. Please specify the nationals’ country of origin, the type of visa or work permit under which they are performing and an explanation of their anticipated level of involvement. You may be asked to provide additional information during negotiations in order to verify the foreign citizen’s eligibility to participate on any contract or assistance agreement issued as a result of this announcement.

ii. Foreign Ownership, Control or Influence (FOCI) companies who have mitigation plans/paperwork in place. Proof of approved mitigation documentation must be provided to Amber Buckley, Contracting Officer, at Amber.Buckley@us.af.mil prior to submitting a white paper and/or a proposal. Defense Counterintelligence Security Agency (DCSA) approved mitigation documentation includes one of the following: Board Resolution; Security Control Agreement; Special Security Agreement; Proxy Agreement;

and Voting Trust Agreement. In addition to providing the approved mitigation documentation, also provide your CAGE Code and your fully executed DCSA cover letter. Expect at least 10 business days for the Government to review and verify FOCI mitigation documentation. Offerors who do not hold one of the above FOCI mitigation documents must work with DCSA to obtain mitigation documentation prior to being eligible under the BAA. For information on FOCI mitigation, contact DCSA.

Additional details can be found at: https://www.dcsa.mil/Industrial-Security/Entity- Vetting-Facility-Clearances-FOCI/Foreign-Ownership-Control-or-Influence/

iii. Foreign Nationals as Employees or Subcontractors. Applicable to any effort not considered Fundamental Research. Offerors are responsible for ensuring that all employees and/or subcontractors who will work on a resulting contract are eligible to do

so. Any employee who is not a U.S. citizen or a permanent resident will be restricted from working on any resultant contract unless prior approval of the Department of State or the Department of Commerce is obtained via a technical assistance agreement or an export license. Violations of these regulations can result in criminal or civil penalties.

c. Information Regarding Non-US Citizens Assigned to this Project

1. Contractor employees requiring access to USAF bases, AFRL facilities, and/or access to U.S. Government Information Technology (IT) networks in connection with the work on contracts, assistance instruments awarded under this BAA must be U.S. citizens. For the purpose of base and network access, possession of a permanent resident card ("Green Card") does not equate to U.S. citizenship. This requirement does not apply to foreign nationals approved by the U.S. Department of Defense or U.S. State Department under international personnel exchange agreements with foreign governments. It also does not apply to dual citizens who possess US citizenship, to include Naturalized citizens. Any waivers to this requirement must be granted in writing by the Contracting Officer prior to providing access. Specific format for waiver request will be provided upon request to the Contracting Officer. The above requirements are in addition to any other contract requirements related to obtaining a Common Access Card (CAC).

2. For the purposes of Paragraph 1, it an IT network/system does not require AFRL to endorse a contractor's application to said network/system in order to gain access, the organization operating the IT network/system is responsible for controlling access to its system. If an IT network/system requires a U.S. Government sponsor to endorse the application in order for access to the IT network/system, AFRL will only endorse the following types of applications, consistent with the requirements above:

a) Contractor employees who are U.S. citizens performing work under contracts, assistance instruments awarded under this BAA.

b) Contractor employees who are non-U.S. citizens and who have been granted a waiver.

Any additional access restrictions established by the IT network/system owner apply.

3. FEDERALLY FUNDED RESEARCH AND DEVELOPMENT CENTERS AND

GOVERNMENT ENTITIES: Federally Funded Research and Development Centers (FFRDCs) and Government entities (e.g., Government/National laboratories, military educational institutions, etc.) are subject to applicable direct competition limitations and cannot propose to this BAA in any capacity unless they meet the following conditions:

a. FFRDCs: FFRDCs must clearly demonstrate that the proposed work is not otherwise available from the private sector; and FFRDCs must provide a letter on official letterhead from their sponsoring organization citing the specific authority establishing their eligibility to propose to https://www.dcsa.mil/Industrial-Security/Entity-Vetting-Facility-Clearances-FOCI/Foreign-Ownership-Control-or-Influence/ https://www.dcsa.mil/Industrial-Security/Entity-Vetting-Facility-Clearances-FOCI/Foreign-Ownership-Control-or-Influence/

Government solicitations and compete with industry, and their compliance with the associated FFRDC sponsor agreement’s terms and conditions. This information is required for FFRDCs proposing to be prime contractors or sub-awardees.

b. Government Entities: Government entities must clearly demonstrate that the work is not otherwise available from the private sector and provide written documentation citing the specific statutory authority and contractual authority, if relevant, establishing their ability to propose to Government solicitations. While 10 U.S.C.§ 2539b may be the appropriate statutory starting point for some entities, specific supporting regulatory guidance, together with evidence of agency approval, will still be required to fully establish eligibility.

FFRDC and Government entity eligibility will be determined on a case-by-case basis; however, the burden to prove eligibility for all team members rests solely with the proposer.

Government agencies interested in performing work related to this announcement should contact the Technical Point of Contact (TPOC). If resulting discussions reveal a mutual interest, cooperation may be pursued via other vehicles.

4. ORGANIZATIONAL CONFLICTS OF INTEREST: In accordance with FAR 9.5, offerors are required to identify and disclose all facts relevant to potential OCIs involving the offerors organization and any proposed team member (subawardee, consultant). Under this Section, the offeror is responsible for providing this disclosure with each proposal submitted to the solicitation. The disclosure must include the offerors, and as applicable, proposed team member’s OCI mitigation plan. The OCI mitigation plan must include a description of the actions the offeror has taken, or intends to take, to prevent the existence of conflicting roles that might bias the offerors judgment and to prevent the offeror from having unfair competitive advantage. The OCI mitigation plan will specifically discuss the disclosed OCI in the context of each of the OCI limitations outlined in FAR 9.505-1 through FAR 9.505-4.

a. Agency Supplemental OCI Policy: In addition, AFRL has a supplemental OCI policy that prohibits contractors/performers from concurrently providing Scientific Engineering Technical Assistance (SETA), Advisory and Assistance Services (A&AS) or similar support services and being a technical performer. Therefore, as part of the FAR 9.5 disclosure requirement above, an offeror must affirm whether the offeror or any proposed team member (subawardee, consultant) is providing SETA, A&AS, or similar support to any AFRL office(s) under: (a) a current award or subaward; or (b) a past award or subaward that ended within one calendar year prior to the proposal’s submission date. If SETA, A&AS, or similar support is being or was provided to any AFRL office(s), the proposal must include:

. The name of the AFRL office receiving the support;

. The prime contract number;

. Identification of proposed team member (subawardee, consultant) providing the support; and . An OCI mitigation plan in accordance with FAR 9.5.

b. Government Procedures: In accordance with FAR 9.503, 9.504 and 9.506, the Government will evaluate OCI mitigation plans to avoid, neutralize or mitigate potential OCI issues before award and to determine whether it is in the Government’s interest to grant a waiver. The Government will only evaluate OCI mitigation plans for proposals that are determined selectable under the solicitation evaluation criteria and funding availability. The Government may require proposers to provide additional information to assist the Government in evaluating the offerors OCI mitigation plan. If the Government determines that an offeror failed to fully disclose an OCI; or failed to provide the affirmation of AFRL support as described above; or failed to reasonably provide additional information requested by the Government to assist in evaluating the proposer’s OCI mitigation plan, the Government may reject the proposal and withdraw it from consideration for award.

5. S&T PROTECTION.

I. Notice of Intent.

(a) Security Risk Review. Each proposal submission will be subject to a Security Risk Review prior to selection for award. The Security Risk Review is applied to federally funded research designed to help protect Department of the Air Force Science and Technology (S&T) by identifying possible vectors of undue foreign influence. AFRL will follow all policy and procedures outlined in Air Force Research Laboratory (AFRL) Instruction AFRLI 61-113, Science and Technology Protection for the Air Force Research Laboratory and Department of the Air Force Instruction DAFI 63-101/20-101, Integrated Lifecycle Management.

(b) Security risk review for these subject proposals will be developed for all proposed Senior/Key personnel and “Covered Individuals”. These risk reviews will be based on information disclosed in a Research and Related Senior and Key Person Profile and Security Questionnaire. In addition, any accompanying or referenced documents, publicly available information, and information contained in internal U.S. Government databases will be utilized in risk reviews. Nationality or citizenship is not a factor in the security risk reviews.

(c) When considering all external engagements, AFRL incorporates a holistic decision-making process that encompasses technical and security factors. The security review method implemented by AFRL measures risk factors to identify the appropriate Risk Acceptance Level (RAL) within the organization.

The objective analysis of the security risk factors is conducted to empower AFRL’s S&T leaders to make risk-informed decisions. The review process generally looks at five factors, or risk areas, but with authority for expanded review as noted in OSD R&E Memorandum dated 6 Jun 2023. The potential security risk factors are set forth below:

Potential security risk factors:

II. Actions Required by Applicants/Recipients at proposal submission.

(a) In accordance with AFRLI 61-113, S&T Protection, Applicants/Recipients are required to submit the following documentation with their proposal:

(1) Grant or Cooperative Agreement (CA) proposals:

(i) Standard Form 424, “Research and Related Senior and Key Person Profile (Expanded) (See

Appendix 1) AND;

(ii) Security Program Questionnaire (See Appendix 2) AND;

(iii) “Privacy Act Statement” consent form for each Covered Individual that is also signed by the Applicants/Recipients as that Individual’s Sponsor. (See “Covered Individual” section below, and Appendix 4)

(2) Contract or Other Transaction Agreement (OTA) proposals:

(i) Research and Related Senior and Key Person Profile Worksheet (See Appendix 3) AND;

(ii) Security Program Questionnaire (See Appendix 2) AND;

(iii) “Privacy Act Statement” consent form for each Covered Individual that is also signed by the Applicant/Recipient as that Individual’s Sponsor. (See “Covered Individual” section below, and Appendix 4)

The above appendices are included in the RI-Specific Proposal Preparation Instructions which can be accessed at: https://sam.gov/opp/5d5947ee115b4a49adc07d0bc4bc72e5/view . Always reference the latest versions of these documents. Complete and submit the required forms with your proposal to the technical point of contact (TPOC) listed in Section VII-Agency Contacts AND AFRL.RIOF@us.af.mil.

(3) In the event a security risk is identified, and the Government has determined the security risk exceeds the acceptable threshold, the Applicant/Recipient will be notified and informed of the decline of award. The Government will only provide a general statement of the reasoning due to Government OPSEC measures.

(4) By submission of the Research and Related Senior Key Person Profile and Security Program Questionnaire, the Applicant/Recipient agrees to comply with the following:

(i) To certify that each covered individual who is listed on the application has been made aware:

1) of all relevant disclosure requirements, including the requirements of 42 U.S.C. § 6605; and 2) that false representations may be subject to prosecution and liability pursuant to, but not limited to, 18 U.S.C. §§287, 1001, 1031 and 31 U.S.C. §§ 3729-3733 and 3802.