From Disparate Sources to Traceable Answers
Connect the systems your organization already operates, resolve their records into one entity graph, and receive answers with their sources attached.
Connection & Fusion
Connectivity Across Existing Systems
20 native connector types across databases, SaaS tools, files, and live streams, each documented in the app.
- PostgreSQL, MySQL, MongoDB, Oracle, and Elasticsearch
- SAP OData, Slack, Google Sheets, and Airtable
- REST APIs, WebSocket streams, Kafka, CSV, and Excel
Mapping Verified Before Any Merge
Each source's schema is detected automatically, then shown to you to confirm or edit before the first sync.
- Automatic mapping on first connect
- A human checkpoint before data is written
One Authoritative Record per Entity
Fuzzy name matching and exact identifiers such as domain, email, and SKU merge duplicates. When sources disagree, source trust and recency decide.
- Exact-identifier matching first
- Conflicts resolved by trust and recency
- Both values kept on record
Search & Query
Natural-Language Queries With Citations
Answers come only from your graph. When retrieval is weak, FRIS asks a clarifying question instead of guessing.
- Grounded only in your data
- Clarifies rather than guesses
Semantic Retrieval
Embeddings over the fused graph, re-generated only when records change.
- Change detection avoids repeat work
- A backfill endpoint for existing data
Relationship Analysis Across Systems
Click into any entity and trace how it connects to records in every source.
- Interactive graph view
- Relationships across every connected source
Trust & Control
Provenance for Every Value
Every fused field records which source it came from, so "where did this number come from?" always has an answer.
- Source recorded per field
- Decisions visible and reversible
Model Cost & Data Handling Control
Use our hosted default, or your own OpenAI, Anthropic, Google, or Azure key. Credentials are stored encrypted.
- Four model providers supported
- Encrypted credential storage
Cost Visibility for Every Query
Every query, sync, and gigabyte of storage is logged with its cost on a live dashboard.
- Per-query cost
- Sync and storage costs
Architecture & Specifications
The technical foundation behind FRIS.
- Backend
- Python and FastAPI, with provider-agnostic model adapters and Docker Compose deployment
- Data stores
- Neo4j for the entity graph, PostgreSQL for the control plane
- Embeddings
- Generated locally inside your deployment
- Frontend
- React, with Cytoscape.js for the graph explorer
- APIs
- REST and GraphQL, plus an MCP server for AI assistants
- Auth
- Accounts with JWT and per-account API keys
- Auditing
- Searchable audit log with a 30-day purge
FRIS Use Cases
See how organizations deploy FRIS across operational roles.
Evaluate FRIS for Your Organization
Identify the systems you need to connect, and our engineers will plan a deployment around them.