Pre-launch

Your agents run 24/7. Who's watching?

Real-time visibility, audit-grade evidence, and execution-time controls so your agents in production don't fly blind.

Request early access → See how it works
agent activity live
The problem

Your runtime wasn't built for things that improvise

Agents plan, improvise, and act with credentials you gave them. Monitoring, IAM, DLP, change management — every layer of your runtime assumes deterministic software. None of it was built for things that decide what to do next.

Shadow agents

“Claude Code, Cursor, agentic IDEs — my engineers run them on company laptops every day. I have no idea what those agents read, where they send it, or what they do with our credentials.”

Head of security · enterprise
The unattributed

“Something deleted a chunk of production data on Tuesday. We can’t tell you who did it — a person, an agent, or which one.”

Engineering lead · incident response
All-or-nothing

“I’d let our finance agent refund anything under $500 on its own. Above that, a human should approve — but there’s no way to set that gate. Today it’s all-or-nothing.”

Head of finance · finance ops
The rogue fleet

“I want to let my team build a fleet of agents that access our data through MCP. I have no way to make sure they all do the right thing beyond the basic security settings.”

Head of operations · platform
How it works

Control where the damage happens

Zakuro sits at the execution boundary — between the agent runtime and the real side effects. At the moment the agent tries to call a tool, use a credential, or reach a destination.

Phase 01
Deploy
Phase 02
Monitor
Phase 03
Enforce
Phase 04
Intervene
Phase 01Deploy
provision + identity

Spin up an agent with its own identity in one command.

~/projects/zak
# Create an agent using the Claude Code or Openclaw template,
# or bring your own
$ zak agent create --name my-agent --template claude-code
# Add API keys to secrets — your agent won’t have access;
# Zakuro manages this securely
$ zak secret create --name llmproxy:llm.api_key --value sk-ant-***
Phase 02Monitor
real-time evidence

Stream every tool call, credential, and network event with audit-grade trails.

finance-bot-7 · activity live
14:31:02stripe.create_refund $4,200pending
14:30:48network → unknown-host.ioblocked
14:30:21slack.post_message #finance-opsallowed
14:30:05postgres.query invoicesallowed
Phase 03Enforce
execution-time policy

Set rules that fire at the moment of action — like requiring approval above a refund threshold.

stripe.create_refund
amount > $500?
no
allow
yes
request approval
Phase 04Intervene
contain + respond

Loop a human in through the tools your team already lives in.

ZakuroAPP2:31 PM
Approval needed · finance-bot-7
stripe.create_refund · $4,200 · cus_Nq4…x8K
Principles

Trust architecture, not promises

ZERO TRUST

Agents are untrusted

The platform never assumes the agent process is benign. An agent may modify itself depending on its access level. Security controls exist at the OS, network, and platform level — not inside the agent.

IDENTITY

Real identities, not service accounts

Agents get first-class identities in your existing infrastructure — Okta, AWS IAM, GitHub — provisioned automatically as part of agent creation. Not service accounts bolted on later.

BYOC

Bring your own compute

Your agents run on your infrastructure. We never see your code, secrets, or data. Zakuro provides the control plane; you provide the compute.

BYOA

Bring your own agent

Run any agent code. The platform's security and identity model works regardless of what's running inside the machine. We provide a default runtime, but it's not required.

Solution

From solo builders to regulated enterprises

Builder

Individual builders

For solo builders running agents with real credentials — you want to see what they’re doing and stop them when they go off.

  • Live timeline of every agent action, in plain English
  • Pause, scope, or revoke in one click
  • Hosted platform — start in minutes, no infrastructure to set up
Get early access →
Most active
Growth stage

Teams scaling agents

For teams moving agents from prototypes into production — where reliability, security review, and customer trust all need to land at once.

  • Per-agent identities and scoping
  • Approval workflows wired into any channel — Slack, Teams, email, webhooks
  • Oversee your team’s fleet of agents with team-wide policies
  • Evidence bundles for vendor review and due diligence
  • Hosted platform — no infrastructure to set up
Get early access →
Enterprise

Regulated industries

For finance, healthcare, government — where every agent action needs a clear owner, a clear policy, and a clear record.

  • Audit-grade evidence with full traceability
  • Execution-time governance across tools, data, and network
  • Workspaces for each team or business unit, with isolated policies and audit boundary
  • Integrates with IAM, SIEM, ITSM, and the rest of your ops stack
  • Bring your own compute — run on-prem or in your own cloud
Talk to us →
Team

We've lived this pain

Between us, we've built detection and response programmes where regulators actually look at the logs, and shipped data products from zero to exit in regulated industries. We know the buyer because we've been the buyer.

Founder / CEO

Product

Built and scaled data products across regulated industries — from zero to acquisition. The kind of work where messy datasets need to become clear UX, and where the wrong data in the wrong hands is a compliance incident, not a bug.

Founder / CTO

Security

Built detection and response programs where the threat model is real and the regulator is paying attention. Currently enabling a company to adopt agentic AI securely — the exact problem Zakuro exists to solve.

What a blocked action looks like up close

The $4,200 refund attempt from the feed above. Zakuro catches it at execution time, captures the full evidence chain, routes the approval, and logs the resolution. Every action, every decision, every second accounted for.

zakuro trace — finance-bot-7 / refund_threshold
14:31:18 action agent: finance-bot-7 │ tool: stripe.create_refund │ amount: $4,200.00 │ customer: cus_Nq4…x8K
14:31:18 policy rule: refund_threshold │ ✕ BLOCKED — requires human approval above $500
14:31:18 evidence trace: 9f3a…c21d │ identity: okta:agent-fin-7 │ context: invoice #INV-20260331-0847
14:31:19 route ⧖ approval request → slack:#finance-ops → @m.chen
14:32:52 resolved ✓ approved by @m.chen — refund executed │ human wait: 93s │ stripe: re_3Nq…pY1
❯

Build with guardrails, not guesswork

We're onboarding design partners now — teams that need execution-time controls before they can put agents in production. If that's you, let's talk.

hello@zakuro.ai → Read the docs