Platform — Decision Intelligence
Decision Intelligence is the analytical layer between discovery and drafting. It generates alignment signals, fit confidence scores, and operational trace data so teams can make informed go/no-go decisions before committing proposal resources.
Most organizations make funding pursuit decisions based on incomplete information — a quick scan of the FOA, a gut feeling about fit, or a deadline-driven scramble. Decision Intelligence replaces that pattern with structured analysis that surfaces what matters before resources are committed.
This is not a black-box AI score. Every signal is traceable to specific criteria, and every confidence level is grounded in identifiable factors that your team can review, challenge, and use to make better decisions.
A structured assessment of how well your project aligns with the opportunity across scope, methodology, budget range, and program priorities. Not a single number — a multi-dimensional signal with identifiable components.
A confidence level that reflects the strength of the alignment signal given the available information. High confidence means strong evidence of fit across multiple dimensions. Low confidence means insufficient data or significant mismatches.
Specific flags for eligibility gaps, budget misalignment, timeline constraints, or scope mismatches that could disqualify or weaken a submission. Surfaced early so teams can address them or redirect effort.
A transparent record of what factors contributed to the analysis — which criteria were evaluated, what data was available, and where uncertainty exists. No black boxes.
The fit diagnostic evaluates alignment across specific, identifiable dimensions. Each dimension produces a separate signal that contributes to the overall assessment.
Does the project's research focus, methodology, and deliverables match the opportunity's stated priorities and technical requirements?
Is the project's expected budget within the opportunity's funding range? Are cost categories aligned with what the program typically supports?
Does the applicant organization meet the eligibility criteria — entity type, geographic requirements, prior experience, and any special qualifications?
Can the project be scoped and submitted within the opportunity's deadline? Is the proposed performance period realistic for the work described?
Does the project address the specific priorities, focus areas, or strategic objectives outlined in the funding opportunity announcement?
Does the team have the organizational capacity, required certifications, and supporting documentation needed to submit a competitive application?
Teams pursue opportunities based on keyword matches and gut feeling
Go/no-go decisions happen in hallway conversations
Misaligned proposals consume weeks of effort before rejection
No institutional record of why opportunities were pursued or passed
Structured fit analysis before any drafting begins
Multi-dimensional alignment signals with traceable reasoning
Risk indicators surfaced early enough to redirect effort
Documented decision trail for institutional memory and review