Iris OS
The first commercial reasoning OS purpose-built for pharma asset launches.
Interpretive competence
Composite cognitive architecture by design that bridges the intuition of generative AI with the absolute, deterministic precision required for compliance.
Trained on causal dynamics
Trained on the causal dynamics of launch success and failure, giving it the foresight to recommend, reason, forecast, and prescribe with commercial teams.
Causally coherent paths
Shift from isolated signals to interpreting combinations of interacting conditions as dynamic business states. Iris recognizes the distinct operating states that emerge when commercial levers — payer, market, field, brand — interact, and simulates how each state evolves under different actions.
Iris OS architecture
Iris is model-agnostic, selecting from the best models built for health, science, and commercial contexts. As models improve, so do our capabilities.
Attest
Attest is priseAI's GxP-grade validation and audit framework for augmented intelligence in regulated pharmaceutical workflows.
It is native to our architecture so that every output from Iris, whether a market access assessment, a prior authorization argument, or a competitive brief, carries an immutable provenance record that answers the four questions any regulator can ask:
What was produced
Every output carries an immutable provenance record.
From what reasoning
Full traceability with composite cognitive reasoning step.
By which state
Model identity, version, and deployment state at inference time.
From what data
Complete data lineage from source through every transformation.
Attest is aligned with 21 CFR Part 11, GAMP 5 Category 5, and the FDA AI/ML Action Plan.
We are happy to share more under NDA.
Approach to model training
priseAI fine-tunes domain-specialized small language models (called “Optimal Alpha” in our architecture) using publicly available data, with each model scoped to a defined operational domain rather than running one general model against every task.
We deliberately do not use continuous or streaming training, which is incompatible with regulated audit trails; instead, our models are validated at defined snapshots and obtain current information through inference-time retrieval against continuously updated graph and vector stores.
The reasoning capability stays stable and auditable while information currency is maintained through architecture, not model mutation.
We are happy to share more under NDA.
See how Iris snaps into your AI fabric. Or build alongside us.
Experience Layer
Chat/voice, web/mobile, SaaS surface, co-pilots
Iris OS
Your other AI solutions
Enterprise AI Fabric / Spine
LLM gateways, vector stores, agent frameworks, knowledge bases, MLOps, etc.
Systems of Record
CRM, ERP, CMS, etc.
Data Foundation & Pipelines
Data lakes, warehouses, ETL, etc.
Put Iris to work today
See how Iris detects, interprets, and reasons across your commercial landscape — in real-time. Book a demo and we'll show you what's possible.