The same thing, recognized once
The same customer shows up in your CRM, your inbox, and your bank feed as three unrelated records. Well resolves them into one entity and keeps the full story attached: 100+ entity types, linked automatically.
Ask anything or use / for commands...
What connected data unlocks
Invoices, transactions, and contacts live in one graph. Hours of manual work disappear.
| Invoice | Amount | Status |
|---|---|---|
 | €5,200.00 | Paid 2m |
 | €1,800.00 | Overdue 12d |
 | €3,400.00 | Partial 1d |
 | €920.00 | Paid 3d |
Know who paid the moment it happens
Every invoice updates to paid, partial, or overdue automatically when a bank transaction lands.
Invoices match themselves
AI reconciles invoices to bank transactions by company name and amount. In seconds, not hours.
One company, one record
Bank feed, inbox, and invoices all resolve to a single entity. No duplicates, no manual cleanup.
Outstanding receivables
€84,250
Cash flow answers on demand
Ask "what's our total outstanding?" and get a real-time answer. No spreadsheet assembly required.
Payment behavior
Days vs due dateSee who pays late before it hurts
Transaction history surfaces early payers, chronic late payers, and who needs a nudge right now.
Who are our late payers this month?
Ask in plain English, get real answers
Questions traverse the full graph, from company to invoice to payment status, instantly.
Legible by default
Raw exports are not context. The graph enriches, scores, and deduplicates every record as it arrives, so what you read is what is true.
Connect. Enrich. Remember.
Logos, tax IDs, roles, and emails arrive filled in. Every entity keeps its history.
Confidence-scored, not guessed
Every field carries a source and a score. Low-confidence values are flagged.
One record per real thing
The same supplier across your CRM, inbox, and bank feed merges into one entity.
Complete context for your agents
An agent is only as good as the context it reads. Well exposes the whole graph, so your AI tools work from the full picture instead of fragments.
MCP server
Plug Well into Claude, Cursor, or any MCP client. MCP here points out: your agents and AI tools read the graph.
REST + graph stream API
Pull entities, relationships, and changes programmatically. Build on the same graph your team works in.
Conversation
Talk to your workspace in plain language. Every reply is grounded in the graph, not a guess.
Web app
Browse, filter, and edit every record. The same context your agents read, legible on screen.
Built on everything you connect
120+ connectors and 11,000+ banks feed the graph. Connect a tool once and its data lands as linked, legible entities.
Frequently asked questions
One connected record of your business: companies, people, accounts, transactions, invoices, documents, and more, linked together and kept current from the tools you connect.
Through the MCP server and the API. Agents read the graph out: entities, relationships, and documents with their full context. Agents draft, and you approve.
Enrichment fills gaps and duplicates merge, each with a confidence score you can inspect. Nothing reaches your other tools without your approval.
120+ connectors and 11,000+ banks, plus email and document drops, flow in through Capture and land as linked entities.