Teams know what was decided, but not why.
Evidence considered, assumptions, alternatives, dissent, authority, uncertainty, and expected consequences are rarely preserved as reusable operational context.
Knowledge Management
Preserve institutional memory as a governed operational asset.
StromaOS captures scientific rationale, evidence, methods, decisions, approvals, commitments, exceptions, outcomes, and lessons across every product, program, study, market, and lifecycle stage.
Always-on cross-lifecycle memoryGoverned evidence and decisionsVisible rationale and uncertaintyReusable qualified knowledge
The institutional memory problem
Pharma preserves documents. It loses the reasoning between them.
Scientific and operational work generates decisions, assumptions, exceptions, rejected alternatives, commitments, approvals, and lessons. Most of that context is dispersed across systems, presentations, meeting notes, email, code, and the memory of experienced employees.
Every new review begins by rebuilding history.
Teams repeatedly search prior analyses, regulatory interactions, study decisions, safety assessments, quality events, market assumptions, and approved content.
Tenured knowledge leaves with people and vendors.
How experts interpret evidence, recognize patterns, challenge assumptions, and navigate exceptions is not captured in executable form.
LLMs can retrieve stale or unauthorized content confidently.
Without source, version, approval, permitted use, confidence, and expiry controls, more retrieval produces more ambiguity rather than better decisions.
The expert moves on either way. What changes is whether the reasoning goes with them - which is why the third study costs less than the first.
Cross-cutting capabilities
One governed knowledge layer across every StromaOS module.
Knowledge Management converts sources, evidence, decisions, rationale, commitments, and outcomes into reusable, permission-aware knowledge objects.
Evidence and rationale preservation
Connect hypotheses, analyses, methods, results, interpretations, limitations, decisions, and subsequent outcomes.
- Source-to-claim lineage
- Method and assumption history
- Rejected alternatives and dissent
- Decision-outcome learning
Process and execution knowledge
Preserve how work was performed, where it failed, what exceptions occurred, how teams intervened, and whether actions worked.
- Workflow and action history
- Risk, issue, and escalation patterns
- CAPA and intervention effectiveness
- Cross-study and cross-market lessons
Common data and meaning model
Connect assets, indications, studies, populations, endpoints, evidence, claims, risks, commitments, markets, and decisions across source systems.
- Shared lifecycle entities
- Ontology and terminology mapping
- Relationship and dependency graph
- Temporal meaning and versioning
Governed decision records
Retain the question, evidence, options, rationale, dissent, authority, decision, action, expected effect, and actual outcome.
- Decision-rights context
- Evidence and rationale traceability
- Commitment and action linkage
- Outcome and lesson capture
Permission-aware knowledge access
Retrieve only eligible knowledge based on role, product, geography, sensitivity, approval state, purpose, and allowed use.
- Source and status filtering
- Role- and purpose-based access
- Current-versus-superseded separation
- Explanation and citation support
Validated institutional reuse
Promote proven patterns, methods, decisions, content, and interventions into governed reusable knowledge without turning every past action into precedent.
- Reusable knowledge qualification
- Confidence and applicability control
- Expiry and revalidation
- Cross-lifecycle propagation
Governed workflow
Move from raw source to reusable institutional knowledge in a controlled sequence.
Every step retains the source, context, version, reviewer, confidence, authority, permitted use, and downstream application.
STEP 01
Capture the source
Data, document, analysis, interaction, meeting, workflow, decision, action, outcome, or expert contribution.
STEP 02
Resolve context
Product, program, indication, study, market, stakeholder, method, question, claim, risk, and time.
STEP 03
Qualify the knowledge
Source status, evidence strength, version, confidence, reviewer, limitations, sensitivity, and authority.
STEP 04
Connect relationships
Claims, decisions, commitments, actions, outcomes, dependencies, contradictions, successors, and superseded items.
STEP 05
Approve reuse
Permitted purpose, audience, module, geography, lifecycle stage, expiry, and revalidation conditions.
STEP 06
Apply and learn
Retrieve, compare, execute, draft, simulate, decide, monitor outcomes, and update institutional memory.
Knowledge readiness
A knowledge object should remain connected to its source, status, authority, and allowed use.
StromaOS does not treat every document or model output as equally trustworthy. Knowledge is qualified by source, version, evidence strength, review, approval, confidence, sensitivity, applicability, expiry, and purpose.
Retrieval becomes safer because the system distinguishes current approved knowledge from draft, exploratory, superseded, disputed, restricted, or expired material.
Model a governed knowledge layerGovernance inside the layer
Institutional memory becomes valuable only when trust, authority, and applicability remain visible.
StromaOS separates source capture, semantic interpretation, evidence qualification, approval, permitted use, retrieval, execution, and promotion into reusable knowledge.
Explore the Governance Spine01
Provenance by default
Every knowledge object retains its source, owner, system, version, timestamp, transformation history, reviewer, and downstream use.
02
Status and authority control
Draft, exploratory, validated, approved, disputed, superseded, restricted, expired, and withdrawn remain distinct governed states.
03
Purpose-bound retrieval
Access depends on role, product, market, sensitivity, intended purpose, decision type, external-use status, and policy.
04
Human knowledge authority
AI may extract, connect, compare, and recommend. Qualified domain owners retain validation, approval, applicability, and reuse authority.
05
Evidence Data Trace
Sources, transformations, prompts, models, versions, reviews, approvals, retrievals, decisions, actions, and outcomes remain reconstructable.
Method routing
Use the right method for each knowledge task.
Knowledge Management routes work through deterministic retrieval, version-controlled analytics, machine learning, local scientific models, governed hosted models, human review, or expert adjudication.
TIER 01Analytical
Search, filters, rules, lineage, status checks, version comparison, relationship traversal, and deterministic retrieval.
TIER 02Statistical
Trend, recurrence, similarity, confidence, evidence weighting, performance, outcome analysis, and qualified workflows.
TIER 03Machine Learning
Classification, clustering, entity resolution, semantic matching, anomaly detection, and model evaluation.
TIER 04Local Scientific AI
Private local models for synthesis, contextual retrieval, controlled summarization, and internal scientific memory.
TIER 05Hosted AI
Approved external models invoked with controlled knowledge, purpose, logging, cost, and output handling.
TIER 06Human
Scientific, clinical, regulatory, safety, quality, legal, operational, and governance review and authorization.
TIER 07Panel of Experts
Structured adjudication for disputed knowledge, conflicting evidence, or high-consequence precedent and reuse decisions.
Governed agent execution
Agents use institutional memory without becoming the authority over it.
Each agent receives a defined knowledge scope, permitted sources, status filters, purpose, intelligence tiers, review requirements, and authority ceiling.
Knowledge orchestration coordinator
Frames the knowledge question, assembles relevant context, reconciles contradictions, tracks gaps, and prepares the governed knowledge package.
- Question and context framing
- Cross-module knowledge assembly
- Contradiction and gap tracking
- Decision-ready knowledge packaging
Retrieval and synthesis specialists
Perform bounded source retrieval, entity resolution, semantic linking, version comparison, evidence synthesis, and knowledge-update tasks.
- Source and relationship retrieval
- Semantic and ontology mapping
- Version and status reconciliation
- Source-linked synthesis
Knowledge governance control
Checks source eligibility, approval status, permitted use, sensitivity, expiry, contradiction, reviewer requirements, authority, and traceability.
- Policy enforcement
- Status and permission control
- Reuse and promotion gating
- Evidence Data Trace
Cross-lifecycle outcomes
Teams move faster because scientific and operational memory no longer has to be reconstructed.
The value is not a larger document repository. The value is governed memory that remains usable inside research, development, regulatory, safety, quality, access, and medical workflows.
Preserve why decisions were made.
Carry forward evidence, assumptions, alternatives, dissent, authority, commitments, expected consequences, and actual outcomes.
Convert tenured knowledge into reusable institutional capability.
Preserve qualified patterns, methods, heuristics, exceptions, interventions, and reasoning without removing human ownership.
Allow meaning to flow across lifecycle functions.
Connect discovery, clinical, regulatory, safety, quality, HEOR, access, and medical work through shared entities and decisions.
Give every agent the right memory, not all memory.
Control retrieval by source, status, role, purpose, product, geography, sensitivity, approval, and allowed use.
Start with one high-value decision domain where teams repeatedly reconstruct the past.
Connect the existing systems and repositories. Define the shared entities, knowledge states, authority model, permitted uses, expiry rules, and outcome links. Then turn institutional memory into a governed operational asset.