agents × cross-enterprise

Enterprise AI agents for cross-enterprise.

One governed agent platform across every business unit — shared connectors, common guardrails, and central observability over legacy stacks and global compliance regimes. The foundation for an AI center of excellence, not another pile of pilots.

Platform standardization Multi-BU governance Legacy adapter layer

A platform, not a portfolio of pilots

At enterprise scale the problem is rarely whether a single agent works — it is sprawl. Every business unit spins up its own bot, on its own stack, with its own security gaps and no shared audit trail. Six months later there are forty disconnected experiments, no one can say which touch regulated data, and the board's AI mandate has produced cost without leverage. The failure mode is fragmentation, and fragmentation is a governance problem, not a model problem.

eeko builds the layer underneath the experiments: a governed agent platform with shared tool connectors, a common retrieval layer, reusable guardrails, and centralized observability that every division builds on. Business units keep shipping agents for their own workflows, but they inherit security, audit, and compliance from the platform instead of reinventing them — turning scattered pilots into a standardized, governable capability and giving your AI center of excellence something real to govern.

A platform every unit builds on.

Three hardened layers, designed for multiple business units and mixed legacy estates.

01 / toolingCORE
Tool-calling into enterprise systems
A shared adapter layer that exposes mainframes, legacy ERPs, modern SaaS, and internal APIs as typed tools — so every unit's agents act through one governed integration surface instead of bespoke point connections.
  • Mainframe + legacy adapters
  • Reusable SaaS & API connectors
  • Central credential & permission broker
02 / retrievalCORE
RAG on enterprise data
A common retrieval layer over each unit's documents and records, with tenant isolation and residency rules built in, so agents are grounded in their division's reality without crossing data boundaries.
  • Per-unit tenant isolation
  • Data-residency-aware retrieval
  • Shared embedding & indexing pipeline
03 / oversightSECURE
Audit, guardrails & human-in-the-loop
Policy is enforced centrally — regional rules, access controls, and approval gates as configuration — while every action across every unit flows into one append-only audit trail for central governance.
  • Centrally enforced policy guardrails
  • Unified, append-only audit trail
  • Per-jurisdiction human-in-the-loop gates

Where AI agents pay back across the enterprise

The compounding returns come from standardizing once and reusing everywhere:

  • Platform standardization — one set of connectors, guardrails, and observability that every business unit reuses, so the second agent costs a fraction of the first and the fortieth is governable.
  • Global compliance enforcement — data-residency and regional rules applied as central policy, so a deployment in one region cannot quietly violate the requirements of another.
  • Legacy modernization — the adapter layer lets agents work across mainframes and aging ERPs without a rip-and-replace, extracting value from systems you cannot easily retire.
  • AI center of excellence — a shared platform, pattern library, and audit fabric that gives a central CoE the tooling and visibility to actually steer AI adoption across divisions.

Common questions.

How do AI agents apply across a multi-business-unit enterprise?

Rather than letting each business unit build its own one-off bots, a cross-enterprise agent program gives you one governed platform — shared tool connectors, a common retrieval layer, reusable guardrails, and central observability — that every division builds on. Units still ship agents for their own workflows, but they inherit security, audit, and compliance from the platform instead of reinventing them, which is the difference between a pile of pilots and a standardized capability.

How do you handle global compliance and legacy systems?

The platform enforces policy centrally while honoring local rules: data residency, regional regulations, and per-unit access controls are configured as guardrails so an agent in one jurisdiction cannot act outside its boundaries. Legacy and modern systems are reached through an adapter layer, so a mainframe, an old ERP, and a SaaS API all present as typed tools, and every action across every unit lands in one append-only audit trail your central governance function can inspect.

Related paths.

Turn scattered pilots into a governed platform.

Tell us how many units are building agents today and on what stacks, and we will scope a shared platform that standardizes connectors, guardrails, and audit across all of them. Response inside 24 hours.