Governed execution for enterprise agents

Across any stack

Connect an AI agent to your real systems safely, control what it can do, and prove every outcome with evidence.

Illustration of a connected enterprise control room

Connect Any System

OpenAPI + Salesforce connectors today, with an extensible framework for more systems.

Deploy Anywhere

Our cloud, customer cloud, or on-prem with hosted or local LLM options.

Flexible Integration

Use the Chat UI directly or embed via Inbound API inside your own app or channels.

One Interface Across Systems

One governed UI and policy layer, without buying separate AI add-ons for every system.

Enterprises run on multiple systems, but agents cannot operate safely across them in production.

Customer data lives across CRM, order management, ITSM, and knowledge bases, not in one place. A user may ask for customer details, latest orders, open tickets, and policy guidance, then ask the agent to start a return. That is where most current approaches break down.

What breaks today

  • Answers are incomplete because data is split across systems.
  • Tools are over-permissioned, so security blocks rollout.
  • Tool execution is inconsistent, causing wrong or partial results.
  • Actions are unsafe without structured validation.
  • No evidence trail means ops cannot debug or prove what happened.
  • Teams end up buying and managing separate AI tools across systems.

What enterprises need

  • A unified answer assembled from all relevant systems.
  • Least-privilege access with only the required endpoints and scope.
  • Deterministic workflows for key reads and all writes.
  • Audit-ready evidence for every outcome.
  • One interface and one governance layer that works across systems.

Real outcomes with guardrails

Multi-intent question and answer

A single request can assemble customer details, recent orders, open tickets, and grounded policy answers from multiple systems in one response.

Example of a multi-intent governed chat response

Return order recipe with deviation handling

Repeatable workflows guide structured actions so a return can be completed reliably with validation and confirmation.

Example of a governed return workflow

See it in action

Zurro.ai user demo video preview Watch the user demo

Zurro.ai user demo scenarios

Watch how governed orchestration, live evidence, recipes, and traceability come together in a real user flow.

Watch on YouTube

Zurro.ai is the control layer between agents and your systems

Answer accurately

Using live system evidence plus approved knowledge.

Access safely

Via least-privilege endpoints and identity scoping.

Execute reliably

Using deterministic recipes for repeatable workflows.

Prove everything

With an Inspector trace showing what ran, why, and the evidence.

One UI plus one API surface. Use the Chat UI for teams, or embed through the Inbound API into your own app or channels. No stack change required - it works across CRM, service, commerce, warehouse, knowledge bases, and custom APIs.

Zurro.ai works from intent to evidence in five steps

01

Understand

Parse a message into one or more user requests and classify the intent.

02

Decide

Use a recipe if available. Otherwise route to governed read-only auto-discovery.

03

Execute

Call only permitted systems and endpoints based on the allowed scope.

04

Respond

Unify the outputs into one human-readable, evidence-backed answer.

05

Prove

Create an Inspector trace for auditability across every decision and outcome.

Two engines plus a learning loop

Engine A - Auto-Discovery

  • Handles questions without a predefined workflow.
  • Read-only by design, governed, and evidence-backed.
  • Pulls data across multiple systems to build a complete answer.

Engine B - Recipes

  • Repeatable exact actions for reads and writes.
  • Removes guesswork so the same request follows the same steps every time.
  • For writes: schema, validation, execute, and full audit trace.

The learning loop

  1. Auto-discovery produces full traces.
  2. The learner proposes recipe candidates from successful discovery traces.
  3. Admins approve and fine-tune before promoting to production.
  4. Result: fewer surprises, faster execution, and more reliable outcomes over time.

Product pillars

Connect

OpenAPI systems plus Salesforce, with an extensible connector framework.

Discover

Auto-discovery answers new questions across systems safely in read-only mode.

Control

Endpoint allowlists, identity scoping, and a secrets vault.

Execute

Recipes for repeatable workflows. All writes run through validation.

Observe

Inspector traces with calls, outputs, evidence, and audit trail.

High level architecture

Zurro.ai high level architecture diagram

Ways to consume

Use Zurro.ai where your users already are

Chat UI

Launch a governed agent experience immediately for internal teams or pilot users.

Inbound API

Embed inside your own product, portal, web, mobile, contact center, or other channels.

Deployment options

Built for enterprise reality

Zurro cloud

Fastest time to value.

Customer cloud

Meet security and data residency needs inside your own VPC or VNet.

On-prem

For regulated environments.

Model flexibility

Hosted or local LLM options, depending on deployment requirements.

Use cases

Customer 360

Profile, orders, tickets, entitlements, and policy grounding in one place.

Self-serve my data only

Order status, returns eligibility, and ticket status using scoped identity.

Validated writes

Create a case or ticket, update address details, and confirm the outcome safely.

Cross-system workflows

Start a return, create the record, get the return ID, create a service ticket, and confirm the result.

Proof and operability

  • Inspector shows intents, selected route, calls made, evidence used, and the final outcome.
  • Logs support QA, debugging, and compliance review.
  • Designed for production operations, not only demos.
  • Turn-based human-readable inspector explanations help teams understand every decision.
Zurro.ai inspector explanation view