1.1 ML & Natural Language Processing Weapon System Info: DIA seeks to improve capabilities and methodologies for leveraging Machine Learning techniques combined with other tools like NLP to automatically identify technical terms and names associated with complex descriptions of weapon systems buried in various types of data sources. These data sources may include raw sensor files, unstructured electronic documents, and various types of multimedia files. These files also may come in various formats. Certain file types may require other pre-processing tools like optical character recognition (OCR) in addition to NLP. Military systems are inherently complex, and weapon systems are often described in various places using a series of letters and numbers and associated “nick names.” Foreign language descriptions, when present, add another layer of complexity. Tools and methods should be able to determine out how to manage dialect and media recognition models associated with weapon systems that are highly unique to the intelligence and military communities. These tools and methods must be able to be applied to and then work with most open source NLP software applications, search tools, and other expert systems. Once organizational expertise has been distilled into knowledge systems that support AI tools, these knowledge systems have to be able to be used to support other AI tools. Once relevant data has been identified, this data will become part of the updated, centralized data model describing the weapon system. Responses to this need can address all or part of this description.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.2 AI & ML Tools, Collection, Research, Monitoring, Automation, Database Development, Data, & Reporting: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to conduct all source collection, research, information monitoring, automated reporting, and database development. DIA seeks tools that streamline and accelerate certain intelligence workflows; to compress intelligence production timelines; to integrate multiple data sets and formats; to identify relationships, connections, correlations, and associations between data; to process data and discern relevance with respect to a given topic; to facilitate information sharing; and to prepare data for anticipatory analysis. These tools must act on large amounts of unstructured data in various formats and potentially accommodate dynamic data flows. AI and machine learning would also support the streamlining and acceleration the more time consuming/intensive tasks of analyzing unstructured information, audio, images/visualizations and video. DIA also seeks to understand industry capabilities for applying artificial intelligence and machine learning to thematic data management and data transformation in a way that allows a semi-automated approach to the extract-transform-load (ETL) burden for collected data. Specific ETL functions include the ability to select, focus, simplify, tag, and transform overtly or covertly collected data into human or machine interpretable form for further analysis or action. Responses to this need can address all or part of this description.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.3 ML Support Workflow Automation: DIA seeks to improve capabilities and methodologies for using machine learning tools to automate intelligence production, planning, and process workflows to reduce the time spent accomplishing these tasks manually.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.4 Tools for Predictive Analysis, Alerting, Indications & Warning (I&W): DIA seeks to improve capabilities and methodologies for applying artificial intelligence, machine learning, and predictive analysis algorithms to I&W within a big data framework. This need will identify semi-automated tools that can conduct analytics of open source data, intelligence sensor data, finished intelligence, financial intelligence, and other forms of intelligence reporting to locate trends, create alerts that require attention, and to recommend actions based upon sensor feeds. Solutions will identify modeling techniques, and will analyze and visually display predictive analytics on changes observed in the battlespace and areas of control during peacetime and during conflict. Specific focus areas include technologies that 1) can manage the expert input often required to make I&W tools leveraging AI and Machine Learning; 2) will have the capability to “learn” from complicated and diverse information flows that are used for I&W; and then 3) will interface with users in a useful way to achieve I&W outcomes (visualization of data, tasking, exploitation, analysis, alerts, and decision support). Responses to this need can address all or part of this description.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.5 Semi-Autonomous Multi-Sensor Fusion Leveraging AI: DIA seeks to improve capabilities and methodologies regarding technology that can leverage AI-enabled sensor processors to manage and fuse multiple sensors of the same or different phenomenology and then to recognize and respond to signature sources by type and to also identify anomalies. The AI enabled sensor network will then predict and respond to recognized threat types and threat activity based upon these sensory feeds. Sensory feeds may incorporate analog and digital feeds from acoustic, seismic, magnetic, density/pressure, electromagnetic, radio frequency, electro-optic/infrared, hyperspectral, and other domain signatures correlated in both space and time.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.6 AI & ML Support to Military Operations: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of fusing Multi-INT sensor data for real-time battlespace awareness and predicative analysis at the strategic, operational, and tactical levels of warfare.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.7 AI & ML Support to Business Operations: DIA seeks to improve capabilities for applying AI and machine learning to the area of business operations to include acquisition management; financial analysis; portfolio prioritization and optimization; business analytics; risk management; resource conservation; and business decision support. The desired solution would enhance the ability to streamline and gain insight through predictive analysis of business financial operations.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.8 AI & ML Support to Data Science: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of a data science environment. CIO is looking for recommendations to identify capabilities that support and streamline Natural Language Processing (NLP) of text and audio data, Recommender Engines, Net Flow Data, and features of the Data Science Environment.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.9 AI & ML Support to Finished Intelligence Products & Knowledge Management: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to scan all finished intelligence products and create from them a body of organized knowledge that people can use to explore topics and concepts. The body of knowledge should return an answer to the user that describes the connections between the data up to the time the user entered the request for information. The solution should return de-duped and de-conflicted data sources to provide analysts a comprehensive end product with accurate sourcing.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.10 AI & ML Support to Open Source Information Gathering: DIA seeks to improve capabilities for using AI and machine learning tools to semi-autonomously collect all forms of open-source information and then updated analytical techniques for data mining and discovery. Solutions should include the ability to combine, compare, and analyze classified and open source material and attempt to cross-verify information obtained from different sources.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.11 ML Support to Management of Tasking from Multiple Sources: DIA seeks to improve capabilities for applying machine learning technologies to the target area of processing incoming tasking from multiple sources, particularly email. This capability prevents tasking from entering an organization without a formal tasking process and helps ensure that ad hoc requirements are tracked and captured by managers. The solution would leverage machine learning tools read email message flows to discover, track, and route tasks to official tasking channels.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.12 AI & ML Support to Dynamic Threat Analysis: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of dynamic threat analysis modeling. Solutions would identify an automated system that will allow analysts to develop weighted analytical threat models leveraging quantified adversary capabilities (either using analyst input or by pulling from existing databases), doctrine, influence, historical behavior, and stated intent.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.13 AI & ML Support to Assessment of Performance Measures: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of assessing organizational performance measures. Solutions will develop a universal performance measurement capability across the Defense Intelligence Enterprise (DIE) to support CCMD and agency priorities.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.14 AI & ML Support to Human Resource Recruiting: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of human resource recruiting. Solutions will be a capability that correlates structured and unstructured data sources to identify, recommend and rank individuals to fill unique billets by leveraging personal biographies, expertise profiles, and available online data.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.15 AI & ML Support to Publication Author Relationships: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of evaluating structured and unstructured data contained within publications to show relationships between authors on a specific topic. Capability should leverage natural language processing to auto tag and build networks based on relationships between authors, coauthors, institutions, topics, and other details.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.16 AI & ML Support to Signature Identification: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of identifying signatures from various sensor sources to aid in exploitation, analysis and production. Signature identification supports Ballistic Missile Technical Collection, Nuclear Monitoring, and MASINT capabilities.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None

1.17 Reserved. AI & ML Support to Records Management: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of front end and back end management of records, business analytics, and visualization.

Current Status: CLOSED

Cutoff Date: To Be Announced

Additional Evaluation Criteria: None

1.18 AI & ML Support to Cybersecurity: DIA seeks to improve capabilities for applying artificial intelligence and machine learning to the target area of cybersecurity. Solution would have the ability to dynamically detect anomalies/risks/threats and then to alert defenders. The capability must be able to perform these functions at a greater scale and pace than what is currently accomplished using the traditional collect, process, and analyze methodology.

Current Status: Open/Considering

Cutoff Date: 25 December 2023

Additional Evaluation Criteria: None



