The shift already happening

AI agents stopped being demos. They became workers.

Put AI agents to work without losing control.

AI agents now call APIs, update real systems, use tools, and touch customer workflows. Zahara approves risky actions before they run, limits what each agent can touch, and keeps a verifiable record of every run.

Built anywhere. Governed in Zahara. Proven when it matters.

Free. No card. About 10 minutes to bring one agent under control.

The new operating problem

Agents stopped being demos. They became workers.

They do not just answer questions anymore. They take action across tools, data, tickets, APIs, and customer workflows, often faster than anyone is watching.

That creates one new problem for every company running them: who controls the agent once it starts acting?

The problem is not that agents are weak. It is that they are strong enough to touch the things that matter.

The pain

Your AI agents are taking actions right now. Could you prove what they did?

Most teams cannot answer the questions that matter.

Missing answer
Which agents are running?
Missing answer
Who owns each one?
Missing answer
What systems can they reach?
Missing answer
Which actions need approval?
Missing answer
What did the agent actually do?
Missing answer
Could we prove it later?

Every one of these is the same missing piece: a layer between the agent and the systems it touches. That is what Zahara adds.

The Zahara answer

Zahara is the operating layer for production AI agents.

Five things, one system: inventory, rules, approvals, monitoring, and proof.

Register every agent

One operating record per agent: owner, purpose, runtime, tools, risk, and status. No more shadow agents nobody tracked.

Set the rules before it acts

Define model routes, credentials, allowed tools, blocked actions, approval rules, and spend limits before trusted work begins.

Approve risky work

Route sensitive actions to the right human before an agent touches customers, money, production systems, or regulated data.

Watch every run

Traces, tool calls, model routes, cost, latency, failures, and outcomes for your whole fleet in one place.

Verify the record

Export the proof and check it yourself. Not just "we logged it." A record you can inspect.

Agnostic by design

Bring your stack. Zahara brings the control.

Use the models, tools, and runtimes you already trust. Zahara does not force your stack. It governs the agent operating contract: who owns it, what it can access, which actions need approval, and what proof is kept after each run.

Any model

OpenAI, Anthropic, Gemini, open-source LLMs, small language models, or your enterprise model gateway. Bring your own keys.

Any runtime

Run the agent in Zahara, your own app, Slack, Teams, a webhook, an API, or a user-owned environment.

Any connector

MCP servers, APIs, databases, SaaS tools, queues, files, and internal systems brought under governed access.

Same controls everywhere

Approvals, credentials, Inspect, Audit, and proof stay consistent even when the agent runs somewhere else.

01Agent
02Model
03Tools
04Gate
05Ledger
06Verifier

Every action passes through control before it becomes work.

Do not trust us. Verify.

Every other governance tool asks you to trust its dashboard. Zahara lets you check the record yourself.

Our own engineer, Thomas, is an AI agent: built on Zahara, governed by Zahara, auditable in Zahara. When we say the loop works, we do not show a slide. We show the record, and you can verify it.

Live proof state

Chain verified

2544 hashed rows. 422 older rows pre-date chaining and are marked as legacy, not tampered.

Hash status
Verified
Retention
3 years
Pricing

Pay for governed capacity. Not every human who inspects the work.

Zahara plans include standalone agents, agent managers, and managed sub-agents. Bring your own model keys and runtime. Zahara pricing covers governance, approvals, audit, and proof - not your model tokens.

Standalone agent
1 unit

A governed agent that acts directly.

Agent manager
2 units

A governed orchestrator that routes work and owns policy.

Managed sub-agent
0.25 unit

A specialist worker under a manager's governance.

Founding 20 - 50% off the first year

For the first 20 teams bringing real agents under control, Zahara offers 50% off Team or Business for the first year in exchange for product feedback, launch partnership, and case-study eligibility.

Capped by count, never by date. The counter shows a real number or no number.

Apply to the Founding 20
Free

Test the full model

$0
Annual: $0

For seeing how Zahara governs real agent work before you pay.

  • 2.5 governed capacity units
  • Enough for 1 manager + 2 managed sub-agents, or 2 standalone agents
  • Vibe Intake, Configure myself, basic approvals, audit, and proof verifier
  • Limited governed actions and retention
Start free
Starter

Build your first governed fleet

$199/mo
Annual: $1,910/yr ($159/mo, save 20%)

For builders and small teams learning Zahara with real agent capacity.

  • 5 governed capacity units
  • Example: 5 standalone agents, or 1 manager + 12 managed sub-agents
  • 10,000 governed actions/mo
  • Credential vault, Inspect, Audit, proof verifier, and basic connectors
Start with Starter
Business

Govern agent teams across the org

$2,500/mo
Annual: $24,000/yr ($2,000/mo, save 20%)

For organizations standardizing agent governance across departments.

  • 75 governed capacity units
  • Example: 30 standalone agents + 5 managers + 140 managed sub-agents
  • 300,000 governed actions/mo
  • Advanced approvals, department views, policy packs, longer retention, and SSO-ready controls
Talk about Business
Enterprise

Custom controls for serious risk

Custom
Annual: Custom

For regulated or larger organizations.

  • Custom governed capacity and action volume
  • SSO/SCIM, dedicated environments, longer retention, and SLA
  • Private/VPC deployment roadmap
  • Security review support
Talk to us
The meter

The only usage bill you can check for yourself.

Every billed action is an audit record. Dispute a line item? Verify the export yourself. The chain settles it.

Bring one agent under control

Prove the loop. Then scale.

Tell us what kind of agent you are moving into production. We will help you choose the right starting point.