An autonomous data team. For every team.
Eisberg's Agent OS is not a chatbot. It is a fleet of governed, identity-bound, audit-trailed agents that automate work across data engineering, governance, data science, business analysis, finance, sales operations, supply chain, customer success, and executive leadership — at the same time, on the same governed data surface.
12+
teams the platform automates work for
<100ms
agent API target on the read path
MCP
protocol native — any agent becomes an Eisberg user
100%
agent actions audit-logged, replayable, revocable
Pick a team. See what stops being a human's job.
The Agent OS is cross-functional by design. Every team in the org gets the same governed data surface — and a different set of agents that automate the work specific to their role.
Pick a team
Data engineering
Pipelines stop paging on-call.
Schema drift detection + auto-remediation
→ Pull-request-style summaries replace 2am pages.
Source-to-warehouse pipeline generation from natural language
→ What used to be a sprint is a 30-minute review.
Per-query routing across the right engine for cost and latency
→ Engineers stop tuning warehouse sizes for every workload.
CDC + streaming pipelines with auto-classification on arrival
→ PII / PCI / PHI never lands ungoverned.
Dependency graph maintenance — orphaned views surfaced and proposed for cleanup
→ Tech debt gets a queue, not a graveyard.
Six guardrails the rest of the industry treats as optional.
Agents are about to become the primary users of every data platform on earth. Most platforms are not ready for that. Ours was designed for it from line one.
Identity-bound
Every agent has its own identity, scoped to a workspace and a resource set. No shared service accounts. No invisible blast radius.
Graduated autonomy
Agents start in advisory mode and earn higher autonomy through verified successful actions. Promotion to auto-execute is policy-gated and revocable.
Per-action metering
Every decision an agent makes is logged with cost, evidence, and policy attribution. Observability and billing share one ledger.
Hard kill switch
Revoke any agent's permissions globally in one API call. Audit log captures who, what, when, and why.
Approval chains
High-stakes actions (writes, exports, policy changes) route through configurable approval chains with webhook integrations to Slack, PagerDuty, ServiceNow.
Policy-as-code enforcement
Agents read the same policy plane as humans. There is no privileged path. Compliance officers audit agent behavior the same way they audit any user.
Agents earn authority. They don't get it by default.
A graduated autonomy model is the prerequisite for trusting any agent with real work. Every level is policy-gated, revocable in one call, and audit-logged end-to-end.
- Tier 1
Observe-and-propose
The agent surfaces what it would do. No actions execute without human approval. Default state for every new agent.
- Tier 2
One-click approve
Agent prepares the action; human clicks to execute. Reduces friction, preserves human-in-the-loop.
- Tier 3
Auto-with-reporting
Agent executes safe, frequent actions and notifies after. Promotion gated by verified track record on lower tiers.
- Tier 4
Full autonomy
Agent acts silently inside its policy envelope. Reserved for narrow, well-understood action types with audit-grade replay.
Promotion between tiers is policy-gated, configurable per action class, and audit-logged end-to-end. Every promotion and every rollback is part of the chain of custody.
Want to see Agent OS run on your team's workflow?
A 30-minute demo against a sample of your real data. We will show agents proposing, executing, and explaining — with the policy plane gating every step.