50+
Hours saved per claims matrix
AI-powered commercial intelligence for life sciences
Emporia transforms clinical and economic literature into compliant, evidence-linked product claims so teams can move faster without sacrificing regulatory confidence.
Built for high-stakes claims workflows
Turn fragmented evidence review into measurable time savings
Emporia helps teams compress query time, accelerate competition analysis, and reduce hours spent on matrix preparation before cross-functional review.
$1.9M+
Annual savings across commercial teams
14%
More relevant outputs than baseline models
Pilot in weeks, not quarters
See how quickly your team can go from literature to launch-ready claims
Book a focused demo and we will walk through your exact workflow: evidence discovery, relevance ranking, and claims matrix generation with citation traceability.
Feature showcase
Three core workflows, one animated product story
Toggle through claims matrix generation, AI literature search, and collateral generation without breaking the flow. Emporia keeps evidence, outputs, and review in one connected system.
Claims matrix generation
Turn complex source documents into structured, review-ready claims
Upload clinical studies, economic analyses, and regulatory documentation. Emporia extracts evidence across multiple PDFs and helps teams move toward a competitive matrix in minutes instead of days.
Multi-PDF ingestionStructured claimsAnnotated review
Key capability
Upload or search documents
Upload up to 10 PDFs (clinical, economic, or technical) in a single workspace, or attach saved abstracts from literature search. Emporia validates and prepares each source so claims are generated from the exact evidence you provide.
Key capability
Generate a claims matrix in seconds
Emporia extracts and structures product claims across your uploaded sources into a unified matrix complete with claim categories, study design, year, source, top authors, and citations.
Key capability
Trace every claim back to the source
After matrix generation, Emporia produces annotated PDFs that highlight the exact text supporting each claim and labels it with the claim number, creating an audit-ready trail for medical, legal, and regulatory review.
Live workflow
How it works
Two evidence paths, one claims workflow
Start with direct PDF uploads or run PubMed search and attach saved studies. Both paths converge into the same matrix generation and evidence-tracking export flow.
01
Search for evidence
Start from your existing sources or discover new studies inside Emporia.
- Path 1: Upload known clinical, economic, or regulatory PDFs.
- Path 2: Run PubMed search in Emporia, review abstracts, and save the strongest studies.
02
Ingest evidence
Bring selected sources into one chat before generation starts.
- Path 1: Upload up to 10 PDFs directly in chat.
- Path 2: Attach saved literature items to chat, including synthetic PDFs when needed.
- Finalize sources before first generation turn, then the source set locks.
03
Generate claims matrix
Use the same output flow regardless of where evidence came from.
- Run Generate Claims Matrix to create structured, source-linked claims.
- Export the matrix and annotated claim-tracking PDFs for medical, legal, and regulatory review.
Data handling and privacy
Enterprise security posture for sensitive life-sciences workflows
Emporia handles clinical and regulatory content with a controls-first approach across data protection, tenant isolation, model governance, and operational visibility.
Current
Data protection and privacy
- TLS in transit and Azure-managed AES-256 encryption at rest (Cosmos DB and Blob Storage).
- Inference-only architecture: customer content is not used to train foundation models.
- 30-day configurable TTL on document metadata with delete-chat cascade across related artifacts.
Current
Access control and tenant isolation
- JWT authentication with RBAC (admin/user) and bcrypt password hashing.
- Short-lived access tokens with refresh-token flow and user-scoped authorization patterns.
- Isolation enforced across storage layers with Cosmos partition keys and Blob path prefixes.
Current
AI pipeline safeguards
- Grounded evidence flow links claims to source passages with citation and page-level traceability.
- Input guardrails enforce query/file limits, PDF type checks, and filename validation.
- Agent runs stateless with bounded tool permissions and no unbounded data access.
Current
Operational security visibility
- Security-relevant auth events and admin actions are logged with actor context.
- Build metadata is embedded in deployments for release and incident traceability.
- Health-check-based deployment model supports stable operations and rapid redeploys.
Our team
Meet the BioStrive team
We build Emporia at the intersection of life sciences and applied AI.
FAQs
FAQs
Emporia currently supports two source paths: direct PDF uploads and saved PubMed literature items (including synthetic PDFs when full text is unavailable). You can combine these in one chat, with a current cap of 10 total sources.
Emporia generates a structured claims matrix from your source set, then runs claim tracking so teams can review annotated source PDFs alongside the matrix.
Each claim is linked back to source evidence through citations and claim-tracking annotations. Teams can open claims and verify supporting passages directly in the source documents.
Yes. You can upload PDFs, attach saved literature items, and generate one matrix from the combined set. In the current product, source setup must be finalized before the first generation turn, after which the source set is locked.
No. Emporia accelerates drafting and evidence organization, but final approval should always come from your internal medical, legal, and regulatory stakeholders. Emporia is built to make that review faster and more consistent, not to replace it.
Emporia aims to produce high-quality drafts grounded in your source documents, but outputs should be validated by your team, especially for nuanced clinical language. The workflow is designed to make verification easy by keeping claims tied to the underlying sources.
Emporia uses TLS in transit, Azure-managed encryption at rest, JWT-based authentication, and user-scoped data isolation patterns across storage layers. Customer content is processed in inference-only mode and is not used to train foundation models.
Yes. Emporia supports matrix exports in CSV and XLSX so teams can share outputs in existing review workflows.
Most teams can generate an initial claims matrix quickly and then iterate through review cycles with significantly less manual extraction work. The biggest wins show up when multiple stakeholders need to verify claims against the same set of sources.
Emporia is built to support life sciences teams of many sizes, from resource-constrained biotech groups to business-unit teams inside large organizations. We typically start with a focused pilot and expand based on results.
Yes, schedule a demo and we can walk through Emporia using your document set. We will also discuss your review workflow so outputs align with how your team approves and deploys claims.
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