Hero — three messages tailored to safety-net leaders
The shift that drives us
Decisions need to arrive faster than the current evidence model can support.
Strategic decisions in the safety-net ecosystem now arrive on cycles the analytical workflow behind them was never designed to keep up with. The questions are the same ones leaders have always carried. The time to defend an answer is what changed — and the workflow producing those answers wasn't built to compress.
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Medicaid coverage shifts since '20.
Public health emergency, continuous enrollment, Medicaid unwinding, work requirements, OBBBA.
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With no dedicated analytics staff.
Across the broader safety net, the bench to support today's analytics needs is not there.
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Rely on safety-net coverage.
Enrolled in Medicaid and CHIP, served by FQHCs, public health departments and others.
5 Medicaid coverage resets have hit the safety net since 2020 — public health emergency, continuous enrollment, Medicaid unwinding, work requirements, and OBBBA.
Two in three local health departments have no staff dedicated to informatics, per NACCHO's 2024 Public Health Informatics Profile. Across the broader safety net — community clinics, FQHCs, and public health departments — the bench that would build today's analyses, dashboards, and grant evidence packs isn't there.
75 million people, enrolled in Medicaid and CHIP, served by FQHCs, public health departments and others.
Where decisions stall
The workflow that informs strategic decisions was built for a slower clock.
The shape of the gap is consistent across organizations. Strategy works on the timeline of the decision. The data work behind it operates on the timeline of the queue. Three places the mismatch shows up:
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When the evidence isn't ready in time.
The biggest moves — entering a market, sunsetting a program, defending a payer rate — get made on the strongest opinion in the room. The information to defend a different answer often exists. It just isn’t there in the window the decision has.
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When questions route through one queue.
Business users submit a request. The most competent data teams still work through long queues. Weeks later, spreadsheets or a dashboard lands, and by then the deadline has moved or the question has shifted. Every strategic question lands in the same queue. The queue runs on a slower clock than the decision does.
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When dashboards arrive without answers.
Today’s dashboards provide data without answers. When your leadership team needs recommendations and the evidence to support them, the gap between data and strategic input is the gap in the workflow.
How it works
Ask. Reason. Answer.
We engineered the analytical process with artificial intelligence. The same steps an analyst takes — compressed from weeks to minutes.
- ▸ What would it take to become the #1 FQHC in the region on colorectal cancer screening?01
Ask
Type questions in plain English. “Which zip codes should we deploy social workers to decrease food insecurity?” “What quality measure are we closest to achieving top performance?”
- Querying UDS — Venice Family Clinic Comparing peer FQHCs in LA County AltaMed identified as benchmark Computing eligible-patient gap Drafting bridge to top performer02
Reason
Agentic analysts leverage governed, authoritative data (Census, HRSA, CDC, CMS, BRFSS) and reason through methodology, findings, and relevance to organization strategic needs.
- CHARTTRENDMAPNARRATIVE
Venice trails AltaMed by 9.1%. Closing the gap = ~1,370 more screened patients.
03Answer
Get true decision support, the evidence, and the next step. Charts, maps, tables, and narratives, ready to drop in a board deck, a leadership conversation, or grant draft.
The platform
The advanced intelligence layer for America's safety net.
Real strategic intelligence. Built on governed, authoritative data your organization already trusts. So more of your budget reaches the people you serve, not the analytics consultant line item.
Conversational intelligence
Ask questions about markets, programs, or populations. Agentic analysts reason across governed, authoritative data and compose strategic answers with charts, maps, tables, and narrative.
Geographic intelligence
Nation-scale coverage with the granular, community-level depth that matters in practice. Define, aggregate, and visualize composite service areas across your organization’s geographic footprint.
End-to-end analyses
An entire analytics team on demand. Hand off complex, multistep analytical requests — community needs assessments, market evaluations, program narratives. Agents deliver decision-ready, interactive findings.
BYOD (Bring Your Own Data)
Combine your internal data — population health, membership, financials, program and operational data — with authoritative external data for community and population-level insights.
The solutions
Decisions, packaged.
High quality, complex analyses safety-net leaders rely on day in, day out. On demand, 10x faster than traditional methods.
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Needs Assessment
Agent-generated analyses, prioritization, needs and asset mapping, and alignment with your organization's strategic objectives. A HRSA-aligned analysis before the end of the work day.
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Market Analysis
Service area demographics, insurance and payer mix, and competitive intelligence that drives business growth and innovation, informs program design, and anchors expansion decisions.
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Grant Evidence
Map health equity gaps, performance improvement opportunities, and population health needs. The defensible evidence layer for grant applications, board reports, and payer conversations.
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Opportunity Scan
An ongoing read of population shifts, unmet demand, and service line opportunities in your catchment area. Real intelligence to inform your growth decision.
The services
When you need a hand on the wheel.
Strategic engagements that pair Thinqpoint's intelligence layer with experienced safety-net and artificial intelligence advisors. For the moments when the platform alone isn't enough.
- Strategic engagement · ongoing
Strategic Advisory
Advisory for your organization's analytics and AI strategy — readiness, vendor evaluation, and governance. Plus the broader strategic questions they touch.
- Analytics + AI readiness assessment
- Vendor evaluation + enablement
- Analytics + AI governance framework
- Strategic engagement · per project
Analytics & AI Engineering
For the moments when the platform isn't the shape of your problem — deep market analyses, custom AI solutions, data engineering. Built to your unique needs.
- Advanced analytics & BI
- AI solution development
- Data engineering & integration
- Strategic engagement · workshops + bootcamp
AI Capacity Building
AI fluency for safety-net leaders, built on three pillars: mastery, safety, and perspective. Anchored by our Executive AI Bootcamp.
- Mastery — deep, adaptable AI skills
- Safety — safe and equitable use of AI
- Perspective — domain expertise, applied
- Strategic engagement · embedded
Pop Health Analytics Leadership
A senior analytics leader embedded part-time, running your population health analytics — risk stratification, segmentation, outcomes.
- Population risk stratification & segmentation
- Outcomes & impact measurement
- Embedded analytics leadership
Ready to see Thinqpoint on your data?
Thirty minutes. Your service area. Your strategic question. We'll show you what an answer looks like.
FAQ
The questions safety-net leaders ask first.
What we hear most often on first calls. Real concerns, plainly answered — no marketing varnish.
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Why aren't you already doing that as part of your job?
They are. Thinqpoint extends your strategy team's reach, not replaces it. Today, your strategy lead pulls Census tables, makes maps in PowerPoint, and waits weeks for the data team. Thinqpoint compresses that work to minutes — so your strategy lead spends their time on strategy, not on data assembly.
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Why should we buy yet another tool? Go work with the data team.
The data team is already overloaded. Right now, requests take weeks and there's no availability for follow-up — the bottleneck is real. Thinqpoint doesn't replace them; it lets your business teams self-serve the routine 80% so the data team can focus on the 20% that needs their judgment. Most customers describe Thinqpoint as 'an extension of the data team' — not a bypass.
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We're not there yet with AI.
Thinqpoint is built around AI but it isn't 'AI for AI's sake.' Every quantitative answer cites the metric, the source, and the methodology — nothing is hallucinated. Your AI governance committee can audit any answer. And you don't need an AI strategy to use it — start with one strategic question, get a defensible answer, and scale from there.
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We already have Tableau, Power BI, Arcadia, or Innovaccer.
Tableau and Power BI are great for the dashboards your team already builds. Arcadia and Innovaccer are great for patient-level population health. Thinqpoint is operational intelligence — the org-level decisions about sustainability, growth, programs, and grants. Different layer, different audience, complementary to what you have.
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What's your HIPAA / BAA / SOC 2 / AI governance posture?
HIPAA BAA available day one. Azure-hosted. SOC 2 Type II on the 12-month roadmap. Full audit trail via pgAudit, 90-day retention. Row-level tenant isolation enforced at the database. Every quantitative answer is provenance-cited — no hallucinated numbers. AI governance documentation available on request.
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How do you handle hallucinations?
Every quantitative answer Thinqpoint produces is grounded in an explicit metric from our annotated catalog. Agents cite the metric ID, variable provenance, vintage year, and methodology. We don't 'estimate' — we retrieve, aggregate with documented methods like Pareto interpolation, and show the lineage. If the system doesn't know an answer, it tells you.
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Will this work on our internal data?
Today Thinqpoint works with external data — Census, HRSA, CDC, CMS, public-health data, market data. That's the right fit for strategic decisions: market entry, program design, grant analysis, equity narratives, service-area planning. Internal-data integration — your EHR, billing, scheduling — is on the roadmap but isn't ready today. If your primary use case requires internal data, let's talk about whether we're the right fit now or a year from now.
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How is this different from ChatGPT?
ChatGPT doesn't know your service area, doesn't have your data, hallucinates quantitative claims, and isn't HIPAA-eligible. Thinqpoint is connected to real Census, HRSA, CDC, CMS, and public-health data; produces provenance-cited answers; composes charts, maps, tables, and narrative together; and ships with a signed BAA. We use LLMs — OpenAI, Anthropic, Google — but we wrap them in a safety-net-specific semantic layer and HIPAA-native infrastructure.