Transform survey responses, narratives, and Video Lab interviews into recruitment-ready insights. AI-powered analysis grounded in what communities actually say.
Every insight traces back to actual survey responses, narrative voices, and recorded interviews — never synthetic data.
Structured responses across 30 metros covering barriers, trust sources, and trial readiness.
Free-text stories about healthcare experiences, embedded as vectors for semantic search.
In-depth recorded interviews with condition-specific speakers, transcribed and categorized.
Problem
Your clinical ops team waits weeks for custom research pulls. By the time data reaches the enrollment strategy meeting, the recruitment window has narrowed.
Built
Ask a plain-English question and get structured insights in seconds — barrier breakdowns, trust patterns, direct community quotes, and strategic recommendations, all validated against real survey responses.
Why It Matters
Collapse the time from "I wonder what communities think about X" to "here's the evidence" from weeks to seconds. Enrollment strategy meetings start with community-grounded data, not assumptions.
Top Barriers in Atlanta
Problem
Site selection relies on claims data and investigator relationships. You're missing the community-level barriers that determine whether patients actually show up.
Built
Heatmap overlays, metro-vs-metro comparisons, and filterable rankings with radar-chart detail. See exactly where transportation kills retention, where trust is highest, and which metros are under-tapped.
Why It Matters
Pick sites where the community is ready — not just where you have PI relationships. Reduce screen-fail rates by matching trial design to local barrier profiles before the first patient is enrolled.
Equity Score Comparison
Problem
Your IRB-approved recruitment flyer says "participate in a clinical investigation." The community says "they want to experiment on us." The language gap is costing you enrollment.
Built
AI surfaces the exact phrases that build trust and the exact phrases that push people away — extracted from thousands of real community narratives, filterable by demographic and metro.
Why It Matters
Rewrite recruitment materials in the community's own language. Teams that match messaging to community voice patterns see higher enrollment and lower early dropout.
What Resonates
Problem
The board asks "how are we doing on health equity?" and your team scrambles to assemble a narrative from disconnected data sources. There's no single number to point to.
Built
Five dimensions — Access, Trust, Trial Readiness, Community Engagement, and Equity Gap — scored per metro with letter grades A through F. Auto-recomputed from live survey data.
Why It Matters
Give leadership a defensible, data-backed equity score for board decks. Compare markets at a glance and direct investment where it moves the needle.
Grade: B+
Problem
Your recruitment team designs one-size-fits-all outreach because they can't see the distinct segments within a community. The skeptics, the advocates, and the caregivers all get the same flyer.
Built
Select a metro and demographic, click Generate, and get 3-4 data-driven composite personas — each with barriers, trust sources, trial readiness, and a synthesized voice quote. Built from real survey narratives, not marketing assumptions.
Why It Matters
Tailor outreach per segment before the first site visit. Teams that design persona-specific messaging see higher enrollment because they address the right fears with the right language for each audience.
Black Community — Atlanta
Quality assurance, intelligent caching, configurable feature flags, and team collaboration — everything a pharma ops team expects from a production intelligence platform.
Every AI response is regression-tested against golden benchmarks. Your team gets validated insights, not hallucinations.
Intelligent query caching delivers repeat insights instantly. Pre-warmed on startup so the platform is fast from the first click.
8 feature flags let you dial capabilities up or down per deployment — topic deep-dives, benchmarks, multi-turn sessions, and more.
Save, share, and pin high-value queries across your team. Build an institutional knowledge base that compounds over time.
Video Lab interviews are processed through an automated pipeline: S3 storage, Amazon Transcribe for speech-to-text, Claude for quote extraction and categorization, and pgvector for semantic search alongside survey data.
Start with a question. ACE Assist will surface the insights that matter — grounded in real voices, not assumptions.