Innovation LabsBring us the decision
Rare disease · Paid build for arachnoiditis
ATLAS Rare Disease
A paid two-stage build that gave a philanthropic buyer a working AI on-ramp and evidence for deciding what should happen next.
Explore the ATLAS engagement mapThis map illustrates a prospective engagement. The completed two-stage build and its findings are documented below.
Evidence before the next commitment
A working tool.
A reason to pause.
A paid two-stage AI build made the next funding decision clearer.
What was the buyer deciding?
Should we fund a larger platform?
A philanthropic buyer wanted to preserve a rare-disease physician’s published knowledge and make it useful to more people with arachnoiditis through AI.
Build a small first form to expose what the larger proposal assumed.
What did FHIL build?
A guided first encounter with the knowledge.
Source-oriented material, a patient-facing starting point and structured prompts, with explicit use boundaries.
- 1
Orient
Begin with the person’s need.
- 2
Bound
Explain limits, privacy and safety.
- 3
Start
Provide prompts and a first action.
- 4
Interpret
Explain what a response does—and does not—mean.
- 5
Act or escalate
Connect information to an appropriate human next step.
Whether a bounded first product could be built. Broad patient usability remained unestablished.
What changed when the idea took form?
Some assumptions held. Others did not.
The first product form worked.
FHIL organized the source material and built a patient-facing starting point. Clinical accuracy and effectiveness were not established.
What did the buyer decide?
Pause further work.
The buyer funded two stages, then paused based on the findings. FHIL recommended preserving the useful assets while examining distribution and paying demand.
Evidence of a viable route to patients—and a payer for the job the product performs.
FHIL’s project account and reusable work
A completed two-stage build
ATLAS Rare Disease is a paid, completed two-stage build for arachnoiditis and is available as the basis for future condition-specific work. The buyer funded two stages and paused further work based on the findings.
A U.S. philanthropic buyer wanted to preserve the published protocols of an aging rare-disease physician and make that knowledge useful to a wider patient community through AI.
The build examined knowledge extraction, clinical and legal boundaries, the usable population, first-use experience, distribution and paying demand.
FHIL recommended preserving the prompts, source framework, patient-facing asset and operating knowledge while the unresolved distribution and demand assumptions were examined.
Evidence boundary: The work established a feasible first product form and informed a funding decision. It did not establish sustained use, clinical accuracy, clinical effectiveness, broad patient usability, scalable distribution, sustainable demand, or population outcomes. Delivery of the tool did not establish an ongoing service with a funded operator.
Open the Arachnoiditis tool — opens in a new tabATLAS Healthspan · In discovery
A foundational framework for a private health-stewardship program. FHIL is in discovery with potential customers; the framework is not a live application.
Preview the Healthspan framework — opens in a new tabBegin a conversation
Choose the level of support the decision requires.
Use the 48-Hour Brief for rapid due diligence. Use the 45-Day Sprint to test one innovation before a larger commitment. Use the Portfolio Review after capital is committed and before the next allocation.