AI Enabled Source Selection Solution for Contract Proposal Evaluation

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Trusted AI and Autonomy OBJECTIVE: Provide a comprehensive software-as-a-service (SaaS) solution that automates and standardizes the evaluation and source selection processes while tailoring the user experience to the Army's unique conditions/constraints. DESCRIPTION: This solution should address principal challenges experienced during the evaluation and source selection processes including length of time required to conduct evaluations; varying levels of experience possessed by evaluators; inconsistent treatment of Offerors by evaluators; and deviation from solicitation instructions and evaluation criteria, potentially leading to protest. This solution is critical to accelerate the overall acquisition process, field capabilities more rapidly to the Soldier, and significantly improve contract outcomes including fewer successful protests. The Army's pursuit of a software solution to automate, standardize, and accelerate the evaluation and source selection processes represents a novel and innovative approach to a challenge traditionally addressed using general-purpose capabilities such as Microsoft Word and Excel or outmoded procurement systems. Additionally, the current processes are heavily error-prone due to individual evaluator inexperience, human mistakes, and evaluator fatigue. The envisioned solution seeks to transform this process by harnessing of the power of AI and related private sector innovations to perform many functions traditionally performed manually by human staff. Many activities in the areas of review, analysis, and quality assurance can be performed at scale by AI and related commercial technologies. Reviewing and analyzing large amounts of evaluation data for inconsistencies, traditionally performed by humans over many weeks, can now be performed at scale through AI tools that perform these functions in just seconds. IMPORTANT: A prize competition, xTechIgnite, will be used to identify small business concerns that meet the criteria for award for this topic. Winners selected from the xTechIgnite prize competition will be the only firms eligible to submit a SBIR proposal under this topic. All other proposals will not be evaluated. See the full xTechIgnite competition details here: https://www.xtech.army.mil/competition/xtechignite/. PHASE I: This topic is accepting Direct to Phase II proposals for a cost up to $2,000,000 for an 18-month period of performance. Proposers interested in submitting a DP2 proposal must provide documentation to substantiate that the scientific and technical merit and feasibility equivalent to a Phase I project has been met. Documentation can include data, reports, specific measurements, success criteria of a prototype, etc. (DIRECT TO) PHASE II: The successful small business should be prepared to rapidly deliver, due to the urgent need for this capability, an initial focused Minimum Viable Product (MVP) thirty (30) calendar days following D2P2 award to demonstrate the maturity and feasibility of their concept. Subsequent to this initial MVP, a series of additional related MVPs in response to additional features requirements will be built to constitute an initial release. During this major research and development effort, the successful small business should demonstrate expert level knowledge of Army acquisition processes, standards, and practices in building a well-defined prototype software product. The desired result at the end of the Phase 2 effort is well-defined prototype of an AI-enabled source selection software solution which automates and streamlines the source selection process from issuance of a solicitation through contract award. PHASE III DUAL USE APPLICATIONS: Currently available private sector solutions applicable to this challenge emanate from large firms such as Appian, CACI, Mantech, and Noblis. In all cases, the evaluation and source selection software market represents a small portion of the large businesses portfolio raising concerns about commitment to the solution. Current commercially available solutions are not tailored to the Federal processes or regulations, and do not leverage the power of an AI-enabled evaluation and source section system and thereby are unsuitable for this challenge. The framework for developing an AI-enabled source selection and evaluation tool in the defense space that is compliant with stringent federal regulations could be applicable to other highly regulated sectors that rely heavily on federal contracts. REFERENCES: 1. https://www.dau.edu/acquipedia-article/source-selection 2. https://ncmahq.org/Web/Shared_Content/CM-Magazine/CM-Magazine-February-2023/AI-Is-Coming-For-Contracting.aspx KEYWORDS: Artificial Intelligence (AI); Evaluation; Federal Acquisition Regulation; Organizational Conflict of Interest (OCI); Blockchain; Neural Networks