The platform that learns your business.
Eisberg doesn't just store your data. It watches your workload and infers how your business actually works from the way your data behaves — the patterns, the exceptions, the joins your people always make — then corroborates it with the tribal knowledge buried in Slack, Confluence, code, and stored procedures. It starts building your business ontology on day one, keeps learning, and serves every agent, every query, and every metric on top of what it has learned. A database gives you tables. A catalog gives you a glossary. Eisberg gives you institutional memory that compounds.
What’s achievable — measured against your real workload
Day 1
the ontology starts working — then learns from every query and correction
Every signal
Queries, actions, classifications, approvals, Slack, Confluence, GitHub, transcripts
100%
Fact provenance auditable; tamper-evident chain on every claim
What ships, in detail.
Continuous capture from every signal your business produces
Every query your team runs. Every action your agents take. Every classification, every approval, every fix. Every Slack thread that explains a metric. Every Confluence page nobody updates but everyone references. Every pull-request comment. Every meeting transcript via Gong / Otter / Recall. The platform captures it as institutional memory — no glossary to maintain, no wiki to update.
Auto-discovered business ontology
Your entities (Customer, Order, Invoice, Engineer, Sprint, Incident, Patient, Trade, Claim — whatever your business runs on) and their relationships are discovered automatically. Tier-graded confidence: high-certainty joins bind on their own, medium-certainty ones queue for human approval, low-certainty ones surface for exploration. Six months of consultant data modeling replaced by an ontology that is useful on day one and learns from every correction after.
Cross-domain stitching — business + software + comms in one
The CustomerImpact entity joining Salesforce.Account ↔ Jira.Issue ↔ Slack.Channel ↔ Zendesk.Ticket. The SprintToRevenue entity joining GitHub.PR ↔ Linear.Issue ↔ Salesforce.Opportunity. Eisberg auto-stitches across your business systems, software systems, and communication systems — discovering relationships no tool confined to a single domain would surface.
Provenance for every fact, signature on every claim
Every term in the knowledge graph carries a source, a timestamp, a confidence score, and a tamper-evident audit chain. Every action by every agent against any fact is signed and replayable. Disputes resolve by replay, not by argument. Regulators replay your AI from the audit log alone.
Ambient enforcement — the rules apply themselves
Captured rules apply when an agent or a human runs a query. When a definition changes, every dashboard, every metric, and every agent that depends on it is re-evaluated automatically — and the lineage shows you exactly what shifted.
Cross-team coherence by construction
Sales, Finance, Ops, Engineering, Compliance, Clinical, and every other function define their own terms. The platform reconciles where they disagree, surfaces the conflicts, and routes them to the human who owns the resolution.
Compounding by design
The longer Eisberg runs, the deeper the moat. Per-customer learning from your workload + cross-customer learning from the network under k≥3 anonymity. Customers 3, 5, 10 each make every other customer smarter — under a privacy-preserving anonymity gate that an incumbent's customer-isolation contract can't match without an architectural rewrite.
Other capabilities that compound with this one.
Want to see it live?
A 30-minute demo against your real data. We'll show you this capability end-to-end and answer any architecture or security question your team has.