$750 refund requested
Support Agent -> Refund API
Action packet createdAI agent control plane
Zahara sits between your agents and the actions that touch money, customers, credentials, and production systems. Rules are enforced outside the prompt, sensitive actions wait for a named person, and every decision leaves a record you can verify yourself.
One control plane for every agent, action, model, approval, and outcome.
Click approve to release the exact amount inside policy. Until then, the agent cannot move the money.
Support Agent -> Refund API
Action packet createdRefunds over $500 require human approval.
Decision: holdSenior Operations approval is required before execution.
Waiting for your clickExecution is paused until the reviewer approves this refund.
Blocked pending approvalThe receipt is sealed only after the approved action completes.
Receipt not sealed yetWhy this matters now
Your agents are already acting. Refunds. Customer emails. Database writes. Purchases. Right now the only thing standing between an agent and a bad outcome is a paragraph of instructions.
A prompt is a request. It is not permission.
Category correction
The market already has strong tools for building agents and strong tools for watching runs. Zahara adds the missing layer: an AI agent control plane that governs who can act, under what rule, with which tools, and how the proof survives afterward.
Good for prompts, flows, tools, and agent assembly. They help teams get agents into motion.
Useful for traces, logs, and activity after the fact. They show evidence, but they do not decide who may act.
Zahara decides what an agent is allowed to do before the action happens, then keeps the proof after.
What the control plane answers
Zahara turns agent operations into governed production work. Before an agent touches production, decide who owns it, what it may use, and where a person must step in. During the run, see what happened. Afterward, verify the record.
Record the owner, allowed tools, and daily budget before production. Tool policy is enforced at a gate outside the prompt, so the agent cannot talk its way past the rule.
Let routine work run. Approval-required capabilities pause and route to a named reviewer. Nothing proceeds until that person approves it.
Follow decisions, tool calls, cost, failures, and handoffs while the work is happening instead of reconstructing it later.
Export the hash-linked record and verify it in your browser. No login. No server call during verification. If a hashed row changed, the verifier identifies the failure.
Proof
Every action links to the policy that allowed it, the person who approved it, and the outcome. Export the chain and verify it in your own browser.
No login. No server call.9c0d7e7b5a9f0d662b8e3f8c1a7d9e6f52361ab5e18b4601e1d50a211c4b8f2a6Built for your seat at the table
Different buyers come in through different problems, but they all need the same thing in the end: an AI agent control plane that makes production agent work governable, inspectable, and safer to trust.
Will this force a rebuild, or can you enforce policy around the agents and tools you already run? Zahara sits outside the prompt, fits the systems you already ship, and gives you a governed path without starting over.
See build and run pathWhat is the blast radius, and who actually holds the keys? Zahara puts credential access behind approval, policy, and least-privilege controls so agent adoption does not become shadow IT.
See security pathCan you trust agents with real customer actions without betting the company? Zahara is built to prove what happened, hold risky actions for review, and make the receipt part of the product.
See founder pathStart with the question that matters to you, then drill into the same proof base: features, verification, docs, and pricing.
Pricing
Agent units combine runtime, action volume, and control-plane capacity, so the plan grows with the depth of agent work you operate.
Prove the control loop with one agent.
For a small production workload.
For teams operating multiple agents.
Once governed agent work moves across teams, the pricing should show operational depth, rollout support, and security controls, not just a bigger number.
For teams standardizing governed agent work across functions.
For complex organizations with architecture, security, and commercial requirements.
Start free, and the first twenty teams also get direct implementation access plus input into how Zahara handles their hardest cases.
Start free and joinStart with one consequential action. Put the control plane between the agent and the real world. Keep proof that survives the dashboard and still holds up later.
Govern your first agent