ICE Enterprise AI_Data and Technology Strategy_RFI.pdf

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ICE Enterprise AI, Data, and Technology Strategy/Arch.:

O&M, Enhancement, and Design RFI Office of Chief Information Officer (OCIO) / Chief Technology Officer (CTO)

REQUEST FOR INFORMATION

Request For Information Overview This is a Request for Information (RFI) for Immigration and Customs Enforcement (ICE), Office of Chief Information Officer (OCIO)

THIS IS A REQUEST FOR INFORMATION (RFI) ONLY. This RFI is on behalf of Immigration and Customs Enforcement (ICE), Office of Chief Information Officer. THIS IS A RFI ONLY. This Request for Information (RFI) is issued solely for market research purposes in accordance with Federal Acquisition Regulation (FAR) Part 10. This RFI does not constitute a Request for Proposal (RFP), Request for Quotation (RFQ), Invitation for Bid (IFB), or other solicitation. The Government is under no obligation to issue a solicitation, award a contract, or reimburse respondents for any costs incurred in preparing or submitting responses. All costs associated with respond‐ ing to this RFI will be solely at the interested party's expense. Responses will be used to assist the Government in acquisition plan‐ ning, market research, and requirements development. The information provided in this RFI is subject to change and is not binding on the Government. All submissions become the property of the Government and will not be returned. If you submit proprietary information, you must clearly mark “PROPRIETARY” on every sheet containing such information and segregate the proprietary in‐ formation to the maximum extent practical from other portions of your response (e.g., use an attachment or exhibit). Respondents are responsible for adequately marking proprietary information in their response. All information received in response to this RFI that is marked “Proprietary” will be handled accordingly. At the sole discretion of the Government, the Government may select sev‐ eral vendors that will be invited to one-on-one sessions with the agency to demonstrate their product and/or services. Vendors who submit responses that are not responsive to this RFI or are outside the scope of what is being requested, will not be consid‐ ered for one-on-one sessions.

Response Due Date: October 16, 2026 @ 10:00 AM, EDT

1.0 INTRODUCTION / PURPOSE

The U.S. Department of Homeland Security (DHS), Immigration and Customs Enforcement (ICE), Office of the Chief Information Officer (OCIO) is issuing this Request for Information (RFI) for market research purposes. ICE is seeking information from industry regarding capable vendors who can provide services across three functional areas supporting the ICE OCIO to help drive purpose‐ ful, mission enablement:

1. Artificial Intelligence

2. Data

3. Technology Strategy / Architecture

These functional areas provide platforms, architecture, standards, governance, strategy, and priority solutions relating to AI, data, and technology enablement across the ICE enterprise - AI Data Technology Strategy (ADTS). ICE is also exploring an enterprise Agentic Software Factory operating model for AI-enabled delivery. For purposes of this RFI, ICE will refer to three related architectural layers, described functionally so that vendors may propose their own implementation approaches, naming conven‐ tions, and product mappings:

Enterprise Control Plane – An enterprise operating model and control plane that converts mission intent into verified, ob‐ servable, and continuously improving production capability. This includes portfolio governance, software factory architecture and infrastructure, supporting reference architectures and grounding material, shared services, enterprise identity and policy, evidence, and cost reporting mechanisms that make up agentic software delivery.

Agentic Orchestration and Runtime Layer – A governed agentic orchestration and runtime layer that coordinates AI and software agents, including model abstraction and routing, task planning and decomposition, tool access, context and mem‐ ory, budgets, and human escalation and stop conditions.

Independent Assurance Boundary – An independent assurance boundary providing functional, integration, cybersecurity, accessibility, and mission acceptance testing, version-bound approval, and release enforcement before production use.

Important: These three agentic software factory layers are reference concepts and desired future-state capabilities, not existing ICE implementations. This RFI is intended both to identify vendors capable of providing O&M and continuous enhancement for ICE's current AI and data capabilities, and to obtain market insight, architectural recommendations, and technical capabilities to design, implement, and operate these three layers over time. ICE’s intent is to operate a secure, modular Agentic Software Factory built by expanding existing STELLA Platform and DevSecOps capabilities, with a design rule that generation, assurance, and authorization must remain distinguishable and no autonomous component may silently expand its own permissions or approve its own produc‐ tion release.

2.0 BACKGROUND

In recent years, the ICE OCIO successfully completed a major initiative to transform ICE into a data-driven enforcement organiza‐ tion through the development of advanced data processes, analytics, and AI capabilities. ICE has successfully designed, developed, and deployed the following capabilities into a production environment, which now require ongoing Operations and Maintenance (O&M) and continued enhancement:

STELLA Platform (Secure Technology Environment for Large Language Agents): A production-ready, multi-cloud (Google, Microsoft Azure, AWS) AI platform with full Authority to Operate (ATO). Built in a Kubernetes-based, containerized infrastructure, it includes LLM proxy, workflow automation, automated AI guardrails, developer workspaces, centralized User Interface (UI), extensive monitoring and logging, and secure access to frontier models across cloud environments.

STELLA Chat: An enterprise-wide, ICE-branded GenAI chatbot equipped with secure web-grounding capabilities and Retrieval-Augmented Generation (RAG) knowledge bases.

STELLA Application Portfolio: A portfolio of 12 fully deployed, production-ready AI applications (low, medium, and high complexity) currently actively supporting ICE's operational and investigative missions.

CORE / TBM Operations: An operational IT Service Catalog, Cost Reimbursement Model, and Technology Business Management (TBM) Spend Dashboards utilizing AI-assisted automation.

Data Lakehouse & Pipelines: Unified data governance layers, automated access controls, and a fully operational Bronze>Silver>Gold data pipeline to curate ICE's data products.

Data Governance: A fully configured Collibra Data Governance Center, ICE Data Inventory, and established metadata tax‐ onomies in compliance with the Evidence-Based Policymaking Act.

API Management & Governance: A centralized, API-led integration layer that securely orchestrates the consumption of governed data products from the Databricks Lakehouse, enabling real-time, compliant data access for the STELLA platform and downstream ICE applications.

AI Governance: Processes and tooling to manage the ICE AI Use Case Inventory process, to include high-impact evaluations and impact assessments.

ICE intends to continue its transformation through evaluation and adoption of new technologies and work patterns. Current ini‐ tiatives include:

Enterprise Agentic Software Factory: Leveraging the STELLA Platform and industry-leading tools and practices to build an enterprise-grade, secure, and auditable Agentic Software Factory, composed of an enterprise control plane, an agentic orchestration/runtime layer, and an independent assurance boundary. ICE intends to:

Own the reference architecture, interoperability rules, evidence model, evaluation harness, and mission measures; and allow industry to compete to supply replaceable capabilities within that framework, avoiding vendor lock-in and keeping integration standards Government-controlled.

Enterprise Architecture (EA) Modernization: Creation of a lean, mission-enabling, AI-driven EA practice focusing on proactive evaluation and standardization of new and emerging technologies and providing the right standards, guidance, tools, and guardrails to project and platform teams in support of the technology strategy and roadmap.

2.0 BACKGROUND (Cont.)

ICE is particularly interested in vendors that can operate within a multi-vendor, modular acquisition posture, in which:

Multiple vendors, models, and deployment environments can coexist;

The Government retains architecture, mission priority, authorization, and risk-acceptance authority; and Government artifacts, telemetry, and evidence are exportable across vendors and clouds.

2.1 Strategic Goals and Mission Outcomes Future acquisitions will prioritize outcomes such as:

Mission delivery: Need-to-capability time, deployment frequency, adoption, and task completion.

Quality: Escaped defects, failed changes, restoration time, and accessibility defects.

Cybersecurity: Vulnerability dwell time, remediation time, exploitability, and patch latency.

Standardization: Reuse rate, approved-path adoption, conformance, and exceptions.

Interoperability: Capability to rapidly compose and reuse modular data services across the enterprise, transitioning from siloed integrations to a plug-and-play mission-agnostic architecture.

Cost and economics: Unit cost per accepted change, release, environment, and mission capability.

AI effectiveness: Acceptance, correction, autonomous completion, and escalation rates.

Governance: Traceability, transparency, auditability, approval latency, exceptions, and prevented releases.

Portability: Time, effort, and cost to replace a model, tool, platform, or provider.

Vendors should be prepared to describe how they would instrument, report, and improve these measures.

3.0 ANTICIPATED SCOPE OF WORK

The anticipated scope of work is divided into the functional areas of AI, Data, and Technology Strategy/Architecture, supporting three distinct but co-dependent verticals under the ICE CTO. Vendors should be prepared to:

Sustain and enhance existing ICE capabilities (e.g., STELLA, STELLA Chat, the STELLA Application Portfolio, data lakehouse, CORE/TBM, Collibra, governance processes); and Help ICE design, implement, and operate the Agentic Software Factory (enterprise control plane, agentic orchestration/runtime layer, and independent assurance boundary) described in Section 2.0 as future-state capabilities.

3.1 Artificial Intelligence

The Government anticipates requiring a vendor to assume full O&M, sustainment, and continuous monitoring responsibilities for the ICE AI ecosystem, including the current platform and STELLA Application Portfolio, and to support the design and build-out of the Agentic Software Factory.

3.1.1 AI Platform and STELLA Application Portfolio Sustainment

Provide continuous O&M and enhancements for the existing STELLA Platform, Agentic Software Factory capabilities as they are developed, and STELLA Chat, ensuring high availability, performance tuning, and patching of the underlying architecture across multi-cloud environments.

Maintain, monitor, and troubleshoot the STELLA Application Portfolio, ensuring ongoing accuracy, relevance, safe autonomy, and interoperability with ICE systems. Vendors should describe how they measure and improve mission performance, cycle time, reuse, and unit-cost economics (e.g., cost per accepted change or mission capability).

Provide Tier 0–3 end-user and developer support from 06:00 AM to 09:00 PM Eastern Time on Government working days, strictly adhering to a < 4-hour initial response time SLA for normal issues and a < 1-hour response for outages. Provide 24/7 on-call support for outages.

Operate within the current environment leveraging common DevSecOps and observability tooling (e.g., CI/CD pipelines, centralized logging, monitoring). Vendors should describe experience integrating with heterogeneous toolchains and main‐ taining a modular, vendor-agnostic tool stack aligned to open interfaces and portability principles, rather than replacing ex‐ isting tools unless explicitly requested.

3.0 ANTICIPATED SCOPE OF WORK (Cont.)

3.1.2 Continuous Enhancements and Agentic Software Factory Alignment

Design, develop, and deploy iterative enhancements to the STELLA Platform, emerging Agentic Software Factory capabilities, STELLA Chat, and existing data and AI architectures, including:

Integrating emerging frontier and specialized models;

Optimizing platform and cloud configurations;

Modernizing developer workspaces;

Continuously evaluating the stack against emerging industry and open-source leaders.

Collaborate with ICE to define and implement Agentic Software Factory layers and components over time, using concepts in this RFI as architectural targets. Enhancements should ensure that agentic/automated development of software, ATO arti‐ facts, security gates, and software delivery:

Enforces bounded autonomy and formal stop conditions;

Provides clear human escalation and override;

Attributes agent actions to identities and authorizations;

Produces portable, machine-readable evidence consumable by independent assurance and authorization systems.

Design and implement governed agentic software factory orchestration and runtime services, including:

Model abstraction, routing, and qualification across multiple providers;

Specialist agents, planning, and task decomposition;

Authorization for tools, context, memory, time, and budget;

Human escalation, stop conditions, and attributed actions;

Evaluation, retry, and multi-agent coordination.

Continuously evaluate and implement UI/UX improvements, new RAG integrations, Model Context Protocol (MCP) integra‐ tions, new feature templates, and tools to improve customer experience and mission value.

3.1.3 Cybersecurity and Information Assurance

Maintain continuous ATO for the current STELLA Platform and the STELLA Application Portfolio; support the Government in designing and operating agentic software factory assurance boundaries. Practices should align with Zero Trust identity, Secure Software Development Framework (SSDF), and relevant DHS/OMB guidance.

Administer and update AI guardrails to protect against prompt injection, data leakage, unsafe autonomy, and misuse, while ensuring tamper-evident logging of user prompts, model calls, agent actions, policy decisions, and AI governance events, consistent with AU-3 and agentic software factory trust-foundation expectations.

Implement and operate an independent assurance boundary over time, consistent with the agentic software factory compli‐ ance concepts, including:

Functional, integration, accessibility, and mission acceptance testing;

Static and dynamic application security testing, software composition and infrastructure analysis;

Policy-as-code, secrets detection, software bill of materials (SBOM) and provenance verification;

AI evaluation, adversarial testing, and misuse analysis;

Version-bound approval, release enforcement, and production verification.

3.1.4 AI Governance and Risk Management

Support the development, implementation, and continuous improvement of enterprise AI governance and risk management processes consistent with applicable federal, DHS, and organizational requirements (e.g., OMB AI memoranda, NIST AI Risk Management Framework, and DHS AI policies).

Support the identification, documentation, assessment, and ongoing management of AI capabilities. This includes executing the intake and review procedures, maintaining the actual data and governance records within the ICE AI Use Case Inventory, and proactively recommending and implementing improved, modernized intake methods or workflow tools to mature the current process.

Provide substantive technical, policy, and risk analysis of AI-enabled systems and use cases, including for high-impact uses of AI, the assessment of applicable governance requirements, risk controls, testing, monitoring, human oversight, and sup‐ porting evidence.

Provide technical and policy analysis of AI-enabled systems and commercial products to assess system capabilities, risks, governance requirements, and the adequacy of supporting evidence.

Support coordination of multidisciplinary AI governance activities, including the development of policies and guidance, tracking of findings and remediation activities, and the preparation of briefing and decision materials for organizational leadership.

3.1.5 Workforce Enablement & Training

Continue administration of the established AI & Innovation Hub.

Update and maintain Standard Operating Procedures (SOPs), end-user training materials, micro-learnings, and video guides as platforms receive routine updates or patches.

Provide workforce training and enablement that explain the agentic software factory concepts and how they will be imple‐ mented over time, including how mission teams can safely use agentic capabilities, interpret evidence and telemetry, and understand autonomy boundaries and escalation paths.

3.2 Data

The Government anticipates requiring a vendor to assume full O&M, sustainment, and continuous monitoring responsibilities for ICE’s enterprise data and analytics ecosystem, while enabling the agentic software factory by providing reliable data and knowl‐ edge capabilities.

3.2.1 Data Operations & Pipeline Sustainment

Maintain and monitor automated data pipelines (Bronze/Silver/Gold architectures) ensuring data quality, ingestion success, and availability for AI modeling and mission analytics.

Provide ongoing administration of the Collibra Data Governance Center and sustain the ICE Data Inventory and Data Dictionary.

Manage role-based access controls (RBAC) and self-service data access portals for registered data products, consistent with Zero Trust identity and classification-aware data routing.

Meet ICE-approved SLAs for data pipeline incident response, data quality issue resolution, and access request fulfillment (e.g. initial response within X hours for priority issues, restoration targets for critical pipelines), to be defined in subsequent acquisition documentation.

3.2.2 CORE & Financial IT Dashboard Management

Centralized Data Lakehouse (integrating Databricks, Collibra, MuleSoft, and Traceable) and the expansion of mission-critical data capabilities. Orchestrating enterprise data governance and providing “white glove” support (e.g., pipeline development, user enablement, data sharing support) Operate an agile "Data Strike Team" model to address tactical, ad-hoc data problems (e.g., legacy system integration, urgent investigative data gaps, or external data curation) alongside persistent "white-glove" support for mission-critical data products.

Sustain and update the IT Chargeback Operating Model, TBM Spend Dashboards (e.g., Power BI), and the OCIO Service Catalog, including telemetry to support the agentic software factory’s unit-cost economics (e.g., cost per data product, per environment, per mission capability).

3.2.3 Enhancements

Expand data lakehouse capabilities by engineering new automated ingestion pipelines for novel enterprise data sources.

Develop and deploy new low, medium, and high-complexity AI applications for the STELLA Application Portfolio as dictated by evolving ICE operational and investigative mission requirements.

3.3 Technology Strategy and Architecture

The Government anticipates requiring a vendor to provide ongoing, proactive technology strategy, enterprise architecture, and technology transformation support to ensure ICE’s AI, data, and application ecosystems remain secure, interoperable, cutting-edge, and aligned with mission and business objectives.

3.3.1 Enterprise Architecture Practice & Technology Roadmap

Operate and mature a lean, AI-driven Enterprise Architecture (EA) practice that aligns ICE’s technology portfolio with mission needs, OCIO strategic goals, and DHS-level directives.

Develop and maintain an integrated technology roadmap covering AI platforms, data lakehouse capabilities, DevSecOps tooling, cloud services, and shared enterprise services, linked to the software factory’s capability categories and mission outcomes.

Conduct regular technology portfolio assessments (e.g., rationalization, duplication analysis, technical debt identification) and provide recommendations to optimize cost, performance, and mission alignment.

3.3.2 Standards, Patterns, and Guardrails

Define, document, and maintain enterprise technical standards, reusable patterns, and “guardrails” that guide project and platform teams in adopting AI, data, and cloud technologies safely and effectively.

Develop and maintain reference architectures and solution blueprints for common use cases (e.g., multi-cloud RAG, agentic AI-enabled applications, secure data-sharing patterns, event-driven architectures) that clearly separate generation/development, independent assurance, and production authorization.

Collaborate with Cybersecurity, Privacy, AI Governance, and Accessibility stakeholders to ensure architecture standards em‐ body security-by-design, privacy-by-design, responsible AI, Section 508, and Zero Trust principles, including separation of duties between generators and approvers.

Provide architecture review and consultation services to program offices, ensuring new solutions adhere to ICE standards, leverage existing capabilities, and avoid unnecessary duplication.

3.3 Technology Strategy and Architecture (Cont.)

3.3.3 Technology Evaluation, Prototyping, and Innovation Support

Assist ICE in designing and implementing the agentic software factory enterprise control plane, including:

Mission portfolio and product governance;

Reference architecture, service catalog, and paved delivery paths;

Enterprise identity, policy, evidence, and cost reporting;

Interoperability, portability, and vendor qualification;

Reusable engineering, data, security, and operational services.

Continuously scan and evaluate emerging technologies for applicability to ICE’s mission. Develop and maintain a technology radar to track and communicate findings.

Conduct structured technology assessments and pilots (proofs-of-concept, minimum viable products) using the STELLA Platform and emerging agentic software factory capabilities to validate feasibility, security, scalability, interoperability, porta‐ bility, and operational value.

Provide objective comparative analyses of vendor solutions and open-source tools, documenting trade-offs related to cost, performance, interoperability, portability, security, and operational risk. Analyses should consider agentic software factory evaluation factors such as mission performance, architecture/interoperability, cybersecurity/supply-chain assurance, agent governance, engineering quality/evidence, lifecycle cost, implementation/workforce adoption, vendor viability, and inno‐ vation value.

Recommend adoption, modification, or decommissioning of technologies based on measurable mission impact, lifecycle costs, and alignment with ICE’s strategic roadmap.

3.3.4 Governance, Compliance, and Portfolio Alignment

Support technology governance bodies (e.g., Architecture Review Boards, Technology Review Boards) by preparing technical briefings, decision memos, and recommendations on proposed solutions and technology investments.

Ensure architectural decisions and standards remain compliant with DHS policies, federal regulations (e.g., Evidence-Based Policymaking Act, OMB guidance), and ICE-specific directives, including applicable OMB AI memoranda, NIST AI RMF and Generative AI Profile, NIST SP 800‑218, and CISA Zero Trust/Secure-by-Design guidance as applicable.

Maintain traceability between strategic objectives, technology standards, individual projects, and deployed solutions to pro‐ vide transparency into how technology investments support mission outcomes.

Provide metrics and reporting on architecture compliance, reuse of enterprise services, and progress toward roadmap mile‐ stones in coordination with TBM and CORE reporting mechanisms.

Develop and maintain EA and technology strategy documentation, including playbooks, guidance documents, and training materials for project teams, developers, and architects.

Curate and maintain a centralized repository of architecture artifacts, patterns, and decision records to enable reuse, knowl‐ edge transfer, and continuity across contractor and government personnel.

4.0 INFORMATION REQUESTED FROM INDUSTRY

Interested vendors are requested to submit responses addressing the following:

Evaluation: The Government recognizes that the proliferation of generative AI tools has made it easier to produce highly polished, technically accurate written proposals. In general, to ensure the Government selects a vendor with genuine, proven capabilities to execute the scope of work, what specific evaluation methods (e.g. live technical demonstrations, code or configuration walk-throughs, scenario-based exercises (tech challenge), site visits, references validation, oral presentations focused on real-world examples) do you recommend to differentiate genuine, demonstrated hands-on capability features creation from purely generative AI responses? In particular:

How would you demonstrate safe failure, evidence quality, recovery behavior, and economic discipline under controlled disruptions such as hallucinated requirements, compromised dependencies, prompt injection, prohibited data-access requests, model outage, cost- or retry-budget exhaustion, failed security/accessibility gates, and human override/rollback?

How would you expose mission performance, architecture interoperability, and agent governance in a way that can be objectively scored against a Government reference baseline?

1.

Enter your answer

Transition-In Experience: Describe your experience taking over the O&M of a large, previously developed AI architecture (e.g. dozens of deployed applications within the STELLA platform) from an incumbent contractor.

How do you approach knowledge transfer and minimizing disruption to mission-critical law enforcement data systems?

2.

Enter your answer

Transition-Out and Continuity: Describe your approach to documenting and institutionalizing knowledge, processes, and artifacts to enable future transition to another vendor or increased government in-housing, while minimizing operational risk.

3.

Enter your answer

Contract Strategy: Given the requirement to balance (1) steady-state O&M of ICE’s AI and data ecosystems, (2) agile, high-intensity support such as “Data Strike Team” missions, new pipeline development, STELLA Application Portfolio enhancements, and agentic software factory enhancements, and (3) ongoing technology strategy and enterprise architecture activities (e.g., roadmap development, standards/guardrails, technology evaluations), what contract vehicles (e.g., GSA MAS, OASIS+) and contract types (e.g., FFP, T&M, Hybrid) do you recommend?

How long should the vehicle(s) be in place?

Should the vehicle(s) have on-boarding mechanisms?

Please provide a rationale based on similar federal environments, including how your recommended approach effectively supports both operational sustainment and continuous technology transformation.

4.

Enter your answer

Pricing Model: What pricing structure (e.g., Firm Fixed Price, T&M, Labor Hour) would you recommend for an effort of this scale and why?

Responses should consider the mix of work, multi-year horizon, and surge activities.

5.

Enter your answer

Reimbursable Cost Modeling: How can the contractor support development of a sustainable reimbursable cost model (e.g., internal chargeback/TBM framework) for Lakehouse and AI platform consumption?

Describe methodologies for accurately capturing, allocating, and reporting on the value and cost-to-serve of individual data products and AI capabilities, including metering units, minimum commitments, tier thresholds, rate limits, overages, premium security features, data-egress charges, observability costs, and exit costs.

6.

Enter your answer

Team Structure and Labor Mix: How should the Government structure the contractor team to manage the distinct workflows of persistent "white-glove" support versus surge-focused "Strike Team" missions with resource plans for operations and maintenance of application features after delivery?

Please recommend an optimal labor mix, key qualifications, feature support lifecycle support, and an organizational structure that avoids role overlap.

7.

Single vs. Multi-Vendor: Does it make sense to pursue multiple vendors to support specific components of the technology stack or lifecycle (e.g. data and knowledge, platform engineering, mission delivery, emerging innovation, independent evaluation/compliance), or is it more efficient to utilize a single vendor for end-to-end integration and O&M across the three proposed verticals (AI, Data, EA)? Provide evidence grounded in federal operations and discuss how your recommended model preserves competition, avoids vendor lock-in, and maintains Government ownership of integration standards and shared technical data.

8.

Enter your answer

Multi-Cloud & AI Platform Sustainment: Detail your technical capabilities in maintaining DevSecOps pipelines, Agentic AI Software Factory operations, LLM proxies, and RAG architectures across multi-cloud environments (AWS, Azure, GCP). Include experience with model abstraction, routing, qualification, and multi-agent coordination in regulated environments.

9.

Enter your answer

Cybersecurity & Information Assurance: Provide examples of your experience sustaining continuous ATOs in multi-cloud federal environments. Describe how you integrate secure-by-design practices, SBOM/provenance verification, Zero Trust identity, policy-as-code, incident response, and separation of generation from independent assurance into your operating model.

10.

AI Governance & Risk Management: Detail your experience supporting enterprise AI governance for federal or similarly complex organizations. Demonstrate proficiency in maintaining AI use case inventories, executing and reviewing AI impact assessments, and conducting technical testing and evaluation of AI models and AI-enabled systems. Describe your ability to inform leadership on AI risks, develop governing policies and guidance, and coordinate multidisciplinary reviews with legal, privacy, cybersecurity, and acquisition stakeholders.

11.

Enter your answer

Portability and Standards: What specific contractual requirements or technical standards should the Government mandate to ensure solutions remain agnostic, facilitating future transitions? In your response, please discuss recommended use of open standards, documentation requirements, and data/model export capabilities to ensure ICE can transition services between vendors, clouds, or in-house teams without material re-engineering.

12.

5.0 Company Overview

Vendors are invited to provide the following contact information:

Company Name13.

Enter your answer

Provide your UEI14.

Enter your answer

Name; Title; XXX-XXX-XXXX; email@email.com

Provide your Contact Information15.

Enter your answer

Small

Other than Small

The Government is considering business size based on the North American Industry Classification System (NAICS) code 541519 “Other Computer Related Services” with a small business size standard of $34M for this effort. The anticipated Product Service Code (PSC) is DA01, IT and Telecom – Business Application/Application Development Support Services. Please indicate one of the following

16.

Small

Woman Owned Small Business

Veteran Owned

Service-Disabled Veteran Owned

8 (a)

HubZone

Other

If number 4 is small, list socio-economic status:17.

mailto:email@email.com

GSA MAS

8(a) STARS III

Alliant 2 Unrestricted

CIO-SP3 Small Business

CIO-SP3 Unrestricted

Veterans Technology Services (VETS2)

None

Other

List any contract vehicles your company holds that would be appropriate for the scope of this work:

18.

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6.0 Response Deadline / Submission Information

RFI/Sources Sought Responses shall be provided by October 16, 2026 @ 10:00 AM, Eastern Time.

Responses shall be submitted utilizing the electronic Microsoft Form. Up to two (2) pages using single space, single sided, 8-1/2 x 11 size, 10pt (or larger) Times New Roman/Arial font, can be submitted if additional space is needed to provide requested informa‐ tion. It is recommended that these additional pages be limited to graphics, diagrams, flow charts, etc. Information shall be submit‐ ted to the ITD Contracting Officer using the subject “RFI # RFI-ICE_ADTS_Sep2026”; e-mail identified below.

The Microsoft Form will automatically turn-off responses at the due date and time of this notice. The date and time will not be ex‐ tended due to failure to complete the form on time.

Questions and requests for additional information must be sent to DHS/ICE via e-mail to: ITD Contracting Officer, at OAQ-ITD-SD-requirements@ice.dhs.gov, by October 5, 2026 at 10:00 AM Eastern Time. All submissions shall include in the subject line “RFI # RFI-ICE_ADTS_Sep2026 – Questions – (Company’s Name).” Phone calls and verbal questions will NOT be accepted or responded to.

Questions shall NOT contain proprietary or classified information. The Government does not guarantee that questions received af‐ ter the due date deadline will be answered.

ICE reserves the right to review late submissions but makes no guarantee to the order of, or possibility for, this review.

All company proprietary information, performance capabilities and/or future modifications must be clearly identified and marked so segregation of proprietary information is required.

mailto:OAQ-ITD-SD-requirements@ice.dhs.gov mailto:OAQ-ITD-SD-requirements@ice.dhs.gov