Secure Research Workspaces
Organize research in private, hierarchical workspaces with authenticated access and layered authorization.
Research intelligence, built on trust
CORIPEX turns document collections into structured, searchable research knowledge. Explore secure workspaces, evidence-aware research workflows, and an AI architecture designed to connect answers back to their sources.
Evidence at your fingertips
Illustrative CORIPEX interface. Actual product screens will be added when approved.
Platform capabilities
One research environment for organizing knowledge, finding relevant evidence, and exploring questions with clear source context.
Organize research in private, hierarchical workspaces with authenticated access and layered authorization.
Bring documents into a controlled processing workflow with malware scanning, isolated parsing, structured metadata, and version-aware content.
Find relevant knowledge using text and semantic retrieval, with workspace-aware scope and source provenance.
Explore evidence-backed question answering designed to connect research findings to identifiable source passages.
Asynchronous processing, durable operation records, and controlled recovery help keep research workflows reliable.
Defense-in-depth controls protect identities, research boundaries, document processing, and access to AI providers.
The intelligence engine
Beyond retrieval. Intelligence by design.
At the heart of CORIPEX is a purpose-built Retrieval-Augmented Generation pipeline, engineered for security, source traceability, and controlled research workflows.
Instead of depending on a generic end-to-end RAG framework, CORIPEX coordinates dedicated components for hybrid retrieval, context engineering, governed generation, and backend-controlled citations. Explore the stages below.
Research begins inside an authorized Workspace. Document identity, version history, and PostgreSQL access rules are preserved before evidence is used by downstream systems.
Term-based retrieval finds passages that match explicit research language while respecting Workspace scope and source eligibility.
Semantic candidates are retrieved from compatible vector indexes. Retrieved records must be rechecked against authoritative authorization and source state.
Reciprocal Rank Fusion combines search channels. A dedicated ContextBuilder selects bounded, diverse, source-linked evidence and limits what may be transmitted to an AI provider.
Model access passes through explicit provider policies, consent, data classification and minimization. Structured generation is coordinated by the application, not by the retrieved documents.
Answer records preserve versioned citations and supporting source references. When the available evidence is insufficient, the workflow is designed to communicate that limitation rather than invent supporting facts.
Architecture explorer — a description of the CORIPEX research pipeline, not a live processing trace.
Interactive demo
Explore guided research scenarios in Biology, Artificial Intelligence, Finance, and Legal Research. Follow the question, inspect supporting material, and see how a source-aware answer is presented.
Architecture & engineering
CORIPEX is built as a security-first modular monolith: clear domain boundaries, a focused deployment model, and independent runtime responsibilities where isolation matters.
PostgreSQL anchors authoritative data and workspace permissions. Redis coordinates background work, while Qdrant supports vector retrieval as a rebuildable index. A governed AI layer separates retrieval, context construction, generation, and source verification.
CORIPEX system architecture
Our engineering principles
Research intelligence deserves more than an impressive answer. It needs secure foundations, traceable evidence, resilient systems, and room to evolve.
Protection is part of the architecture, from private workspaces and database-level isolation to secure document intake and controlled AI access.
Research starts with sources. Retrieval, provenance, and citations are designed into the workflow rather than added as an afterthought.
Documents, metadata, and source history remain authoritative; indexes and AI components can evolve around them.
A focused modular core today, with explicit boundaries for more sophisticated capabilities tomorrow.
Designed to be tested, reviewed, and improved. Versioned data, automated checks, independent reviews, and failure-aware workflows are part of how CORIPEX is engineered.
What's next
CORIPEX continues to evolve from a secure research workspace into a more capable research intelligence platform. Each new capability builds on a foundation designed for secure, explainable, and reliable AI.
Research foundation
Secure workspaces, document intelligence, traceable data, retrieval, and source-aware research workflows.
Under development
More refined research interactions, guided analysis, improved context awareness, and richer ways to inspect supporting evidence.
On the roadmap
Research agents, multi-model orchestration, deeper quality evaluation, and more sophisticated research briefs.
Future vision
Knowledge graphs, richer collaboration, organization-level features, and scalable cloud experiences.
More to come
Product walkthrough
A guided product walkthrough is on the way. In the meantime, explore the interactive research demo.
Explore Interactive Demo →Built with modern engineering tools
A practical, modern stack chosen for clear responsibilities: a secure application core, a responsive research interface, reliable data and task infrastructure, and a replaceable AI integration layer.
Python · FastAPI · Pydantic · SQLAlchemy · Alembic
React · TypeScript · Vite · TanStack Query
PostgreSQL · Redis · Qdrant · Dramatiq
Docker · Docker Compose · GitHub Actions
PostgreSQL RLS · ClamAV · Argon2id · pytest · Ruff · mypy · Gitleaks
Get in touch
Interested in CORIPEX, its architecture, or the ideas behind the platform? Contact us at info@coripex.com.