Built on InnMap’s real-world medical protocols, InnGene supports the full personalized medicine flow: patient understanding, pathway-driven diagnostics, processing of findings, clinical recommendations, and continuous physician-guided iteration.
records · files
structured intake
labs · imaging · genomics
preserve · normalize · connect
diagnostics · treatment · supplements
what to test · what to recommend
pathway-driven workup
treatment + supplements
EHR · apps · wearables
InnGene’s value comes from the combination of proprietary medical methodology and sophisticated engineering architecture. It is designed to support the entire personalized medicine workflow, not only a single preparation step.
InnGene is grounded in InnMap’s diagnostic, treatment and supplement protocols developed and refined through real patient practice — not just generic medical model knowledge.
The system uses structured patient modeling, staged reasoning, knowledge assets and protocol-driven orchestration. The engine is designed as infrastructure, not as a single prompt over documents.
InnGene supports patient understanding, diagnostics, interpretation of new findings, personalized recommendations and physician review — keeping the whole flow coherent across time.
InnGene is a standalone engine that can connect to multiple systems. Inside it, proprietary InnMap protocols combine with structured data layers and AI reasoning to produce physician-ready diagnostic and treatment intelligence.
source or destination
intake & engagement
biomarker data
continuous inputs
the continuously evolving clinical representation
structured relationships between findings and interventions
diagnostic · treatment · supplement logic
staged reasoning around explicit medical structure
physician-ready outputs
review and approval
discussion and rationale
interventions & supplements
backend for other products
InnGene encodes InnMap’s tested personalized medicine protocols into a form that can scale across physicians, clinics and products.
It helps across the full cycle: patient understanding, diagnostics, reasoning on new findings, recommendations and physician review.
It can connect to EHRs, apps, wearables and partner products — making it a reusable intelligence layer, not a one-off feature.
The system structures, reasons and drafts. The physician reviews, approves and remains fully responsible for the medical decision.
The bottleneck is not one isolated task. It is the entire flow: unclear pathways, fragmented patient evidence, hard diagnostics, difficult synthesis of findings, and difficult recommendation generation as new data continuously arrives.
Many clinics rely on individual physician expertise rather than on an explicit, repeatable personalized medicine operating system.
Patient history, questionnaires, labs, biomarkers and genomics need to be continuously connected, not handled as isolated events.
True value lies in deciding what to test, what it means, what to recommend and why — all inside a coherent physician-ready workflow.
It does not stop at summarization. It turns raw data into a patient model, applies InnMap’s proprietary clinical logic, supports diagnostics, processes incoming findings, generates treatment and supplement recommendations, and keeps the reasoning chain structured for physician review.
InnGene’s core value comes from combining AI with explicit medical structure: longitudinal patient representation, clinical knowledge assets, proprietary pathways and staged reasoning.
Long context does not guarantee reliable recall. InnGene separates exhaustive evidence extraction from later reasoning, so the system does not prematurely discard clinically meaningful details before enough context exists to judge them.
Generic LLMs are not enough when the clinic’s methodology is the product. InnGene makes that methodology explicit and machine-operable — so output reflects InnMap’s way of practicing medicine, not only the model’s generic prior.
As models improve, durable value compounds in the protocol layer, the patient representation, the knowledge graph and the feedback loop from real clinical use.
Proprietary pathways for diagnostics, treatments and supplements developed from real patient workflows.
Patient context becomes a reusable evolving state, not a one-off prompt assembled from scratch each time.
Structured relationships connect conditions, biomarkers, interventions and recommendations across the flow.
Extraction, diagnostics, recommendation generation and iteration are separated into purposeful system stages.
Physician review and real patient cases create continuous opportunities to refine protocols and knowledge structures.
The same engine can power clinics, partner physicians, health apps and new patient-facing products.
Separating InnGene from a single workflow expands the opportunity from service efficiency into scalable distribution of personalized medicine intelligence.
Clinics, physician networks and digital-health products can all use the same medical intelligence core while keeping their own workflow, user interface and distribution layer.
InnGene combines real clinical methodology with scalable software architecture to support diagnostics, recommendations and continuous patient reasoning across the entire personalized medicine flow.
Partner with InnGene