Y26-04-RFI_AI-Assisted_Environmental_Monitoring_&_Response.pdf
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- Solicitation number
- Y26-04-RFI
- Issued by
- Orange County, Orlando City, Florida
About this file
This is a Request for Information (RFI) issued by Orange County, Florida's Procurement Division seeking vendor capabilities for AI-assisted environmental monitoring and response solutions. Orange County is exploring artificial intelligence tools to enhance environmental monitoring, detect environmental risks early, identify water quality issues and harmful algal blooms, and prioritize field inspections to support faster response and proactive environmental protection. The County seeks information from vendors capable of analyzing environmental data, sensor streams, and imagery from sources including water quality sensors, satellite imagery, aerial imagery, drone data, and historical monitoring records. Electronic responses must be submitted through the OpenGov Procurement Portal by 4:00 PM EST on Tuesday, March 31, 2026, with no alternative submission methods permitted. Patricia Rigby, Buyer, serves as the point of contact (Patricia.Rigby@ocfl.net). This is an informational RFI only, and no awards will be made from this solicitation.
Respondents must address ten key areas: vendor background and experience implementing AI solutions for environmental monitoring, system capabilities for data collection and analysis, data source and integration capabilities with existing county systems, AI model governance and transparency mechanisms, security and data management protocols, implementation and deployment timelines and infrastructure requirements, performance metrics and reporting functionality, cost and pricing models with estimated ranges for county-scale implementation, innovation and future capabilities, and pilot program opportunities. No specific funding amounts, pricing terms, or award values are established, as this is an informational solicitation rather than a competitive procurement. No set-asides, disadvantaged enterprise requirements, or incumbent vendors are identified. Responses must utilize the County's standard response forms without modification and submit all files in commonly accessible formats (Microsoft Word, Excel, PowerPoint, or Adobe PDF) without security or password protection, with scanned documents meeting a minimum quality standard of 150 dpi. Vendors bear full responsibility for ensuring timely submission through the designated platform.
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Text version
Issue Date: March 17, 2026
ORANGE COUNTY FLORIDA
PROCUREMENT DIVISION
REQUEST FOR INFORMATION #Y26-04-RFI
FOR
AI-ASSITED ENVIRONMENTAL MONITORING & RESPONSE
Copies of this Request for Information document may be obtained from Orange County by download at: https://secure.procurenow.com/portal/orangecountyfl
SUBMISSION DUE DATE:
Electronic responses will be accepted up to 4:00 PM (local time), Tuesday, March 31, 2026, via the electronic procurement portal referenced above.
Electronic submissions are required to be made through the OpenGov Procurement portal only at:
https://secure.procurenow.com/portal/orangecountyfl.
NOTICE TO RESPONDENTS:
Your point-of-contact for this solicitation is Patricia Rigby, Buyer at Patricia.Rigby@ocfl.net.
OVERVIEW:
Orange County, Florida is exploring artificial intelligence tools to enhance environmental monitoring, early detection of environmental risks, and prioritization of inspections. The County seeks information from vendors capable of analyzing environmental data, sensor streams, and imagery to identify potential water quality issues, harmful algal blooms, and other environmental concerns in order to support faster response and proactive environmental protection.
NO AWARD WILL BE MADE FROM THIS SOLICITATION.
THIS IS A REQUEST FOR INFORMATION ONLY
https://secure.procurenow.com/portal/orangecountyfl mailto:Patricia.Rigby@ocfl.net
REQUEST FOR INFORMATION
RESPONSE FORM AND MARKET/PRODUCT QUESTIONNAIRE
RESPONSE FORM
THE FOLLOWING SECTION MUST BE COMPLETED BY ALL RESPONDENTS:
Company Name:
(Street No. or P.O. Box Number) (Street Name) (City)
(County) (State) (Zip Code)
Contact Person:
Phone Number:
Email Address:
[REMAINDER OF THIS PAGE INTENTIONALLY LEFT BLANK]
MARKET/PRODUCT QUESTIONNAIRE
1. VENDOR BACKGROUND AND EXPERIENCE
a. Describe your organization’s experience implementing AI or advanced analytics solutions for environmental monitoring, including water quality, stormwater management, or ecological protection.
b. Provide examples of deployments with local governments, environmental agencies, or utilities.
c. Provide case studies demonstrating how AI solutions have improved environmental monitoring, incident detection, or regulatory compliance.
d. Identify any experience supporting water quality monitoring, harmful algal bloom detection, stormwater inspection prioritization, or watershed management.
2. SYSTEM CAPABILITIES
Environmental Monitoring
a. Describe how your solution collects and analyzes environmental data from sources such as:
o water quality sensors o satellite imagery o aerial imagery or drones o environmental reports from residents o historical environmental monitoring data
b. What types of environmental indicators can the system detect or monitor (e.g., nutrient levels, turbidity, algae bloom indicators, stormwater runoff patterns)?
c. Can the solution support real-time or near-real-time monitoring of environmental conditions?
AI-Based Risk Identification
d. Describe how AI models identify potential environmental risks or anomalies, such as emerging water quality concerns or algae bloom conditions.
e. Can the system analyze historical environmental data to predict areas of elevated environmental risk?
f. Does the platform provide early warning alerts to environmental staff when conditions indicate potential environmental incidents?
Inspection Prioritization
g. Describe how the solution can assist in prioritizing field inspections based on environmental risk factors.
h. Can the system automatically identify locations that may require investigation or enforcement actions?
i. Does the platform support automated task assignment or inspection scheduling based on risk analysis?
3. DATA SOURCES AND INTEGRATION
a. Describe integration capabilities with existing environmental monitoring systems, water quality databases, or GIS platforms.
b. Can the system integrate with county GIS systems to visualize environmental risks geographically?
c. Can the solution ingest data from IoT environmental sensors or monitoring equipment?
d. Does the system support integration with drone imagery or satellite data sources?
4. AI MODEL GOVERNANCE AND TRANSPARENCY
a. What AI techniques power the environmental monitoring solution (e.g., machine learning, computer vision, predictive analytics)?
b. How does the system ensure accuracy when identifying environmental risks or anomalies?
c. Can the system provide explainable insights or supporting data for AI-generated alerts?
d. What mechanisms allow environmental staff to review, validate, or override AI-generated findings?
5. SECURITY AND DATA MANAGEMENT
a. Describe how the system manages environmental monitoring data and associated imagery.
b. What cybersecurity protections exist for government data and sensor networks?
c. What compliance standards does the solution support (e.g., SOC 2, FedRAMP, or other government security frameworks)?
6. IMPLEMENTATION AND DEPLOYMENT
a. What is the typical deployment timeline for an AI-based environmental monitoring system?
b. What infrastructure or equipment may be required to support implementation (e.g., sensors, drones, cloud services)?
c. What data sources would the County need to provide for initial model training?
d. What training is required for environmental staff and system administrators?
7. PERFORMANCE METRICS AND REPORTING
a. What key performance indicators are typically used to measure success for environmental monitoring AI systems?
b. Can the system provide reporting on:
o environmental incidents detected o response times o inspection prioritization effectiveness o environmental trend analysis
c. Can the system generate visual dashboards for environmental monitoring and decision-making?
8. COST AND PRICING
a. Provide estimated cost ranges for implementation at a county scale.
b. Describe your pricing model (subscription, sensor-based licensing, or usage-based).
c. Identify ongoing operational, maintenance, or data service costs.
9. INNOVATION AND FUTURE CAPABILITIES
a. Describe emerging capabilities such as:
o AI-driven watershed modeling o predictive environmental compliance analytics o automated drone monitoring o climate resilience modeling
b. How could the solution support long-term environmental planning or climate adaptation strategies?
10. PILOT PROGRAM OPPORTUNITIES
a. Would your organization support a pilot deployment focused on selected water bodies or environmental monitoring zones?
b. What resources would be required from the county to conduct a pilot?
c. What evaluation metrics would you recommend for measuring pilot success?
REQUEST FOR INFORMATION #Y26-04-RFI
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