Not a best guess. A deterministic proof of exactly what your change does to the live network.
Every path computed against your live topology, so a change is proven safe, or blocked with the reason, before it ships.
Allow app-sg egress to any destination
No more hand-crafting CLI at 2 a.m. Tell Config Studio what you want in plain English. It finds the fault, writes the vendor-correct fix, and proves it safe on a model of your live network before anything ships.
Every change to your network runs the gate first: simulated on your live topology, proven safe or blocked, before it ships. Here is a real run.
Point it at your configs and ask what a change will do. Reachability and traceroute across every major vendor, answered in milliseconds.
When a config breaks, it finds the fault, writes the fix, and proves it safe in simulation — before anyone approves it.
Config Studio computes exactly what a change does to every path in your network, then shows the routes and rules behind the answer. If it can't prove a change safe, it blocks it.
One graph spans them all. Ask "what can reach my database from the public internet right now," and get a real answer.
Reachability is modeled across on-prem, every major cloud, Kubernetes, and the service mesh as a single graph. A change in one domain can't quietly open a hole in another.
One change. See every service it puts at risk, and the "redundant" path that secretly isn't, before it ships.
Optimesh runs on every pull request that touches network config. A red verdict fails the check and blocks the merge, with the offending rule cited right on the diff. No green check, no ship.
Every verified change writes its proof back to the change record. The reviewer sees the verdict, the reachability diff, and the cited rules without leaving the ticket. Audit gets a reproducible artifact instead of a screenshot.
terraform plan tells you what will change. Optimesh tells you what it will break. Drop it into any pipeline as a step that reads the plan and proves the resulting network still holds its invariants.
Built for the security team that has to sign off. Runs where your network runs, changes nothing without a human.
Runs entirely inside your environment. Configs and state stay on your hosts. Works fully offline with a self-hosted model.
Reads configs; it does not push. Applying is a staged write with a human approval and auto-rollback.
An AI proposes the fix, but a deterministic engine decides if it's safe. The model can never reach "deploy" on its own.
OIDC single sign-on, role-based access, and an audit event with before/after hashes on every apply.
Offline checks mapped to STIG, CIS, NERC, HIPAA, and PCI run on every snapshot, no model required.
Baselines your intended state and flags drift the moment a device diverges from the source of truth.
Each one alone would justify a new category of tooling. Arriving together, they make verification non-optional.
Cisco reports 165,000+ agentic workflow executions monthly. AI is no longer drafting suggestions, it's executing changes on live networks, clusters, and clouds.
Every major AI agent ships without a deterministic verifier between the model and production. We built the platform that proves an AI-proposed change is safe before it executes.
The EU AI Act, effective August 2026, mandates auditability and human oversight for high-risk AI. Infrastructure agents fall squarely in scope.
Enterprises want autonomous operations but won't let AI change things unsupervised. Deterministic verification closes the gap: the agent proposes, the verifier proves.
| Approach | Prevents the bad change | Runs at CI speed | Verifies AI output | Runs on your hardware |
|---|---|---|---|---|
| Monitoring & observability | — | — | — | partial |
| Legacy verification tools | partial | — | — | partial |
| Intent-based networking | partial | partial | — | partial |
| AI copilots & config assistants | — | partial | — | — |
| Optimesh | ✓ | ✓ | ✓ | ✓ |
Hammerhead verifies network, Kubernetes, and cloud changes; Config Studio adds AI diagnosis and remediation. Both run on your hardware today.
Purpose-built appliances with local AI inference and deterministic verification, the autonomous network engineer that never sleeps.
Verification for every AI agent acting on any infrastructure: Terraform, databases, CI/CD, and beyond. The trust layer becomes the standard.
From the Optimesh founders, on verification, the shift to AI-driven operations, and where the field goes next.
High-risk AI now needs auditability and human oversight. Infrastructure agents are squarely in scope, and "the model was confident" is not a control an auditor accepts.
Read the noteOptimesh builds offline intelligence so the engineers routing the world's traffic know exactly what a change will do before they make it.
Flight systems for lunar landers. The satellite network connecting the planet. Platforms at billions-of-users scale. The people who spent a decade proving the impossible correct are now doing it for the network.
An entire network's forwarding plane, simulated in milliseconds. 99.93% parity with the industry standard, 800× faster, on a laptop.
The first network teams run verified change on their own fabrics, on their own hardware. Nothing leaves the building.
Config Studio diagnoses the fault, writes the fix, and proves it safe before a human ever approves it.
Operators who have run real networks, angel investors, and NVIDIA's startup program bet on the thesis.
Selected for the program. We chose to keep building independently, focused on shipping the platform.
Deterministic verification for every AI-driven change to any infrastructure. Software today. Purpose-built hardware next.
Verification is the groundwork. Next: an agent that runs your network end to end — diagnosing, fixing, and proving every change safe on its own, with humans only on the calls that matter.
Cross-validated against industry-standard analysis and a live routing stack. Every output deterministic. If the data doesn't support the claim, we don't make it.
Whole-fabric simulation in milliseconds. Validation runs on every commit, not once a quarter.
Runs entirely on your hardware. On-prem and air-gap ready. Your configs never leave the network.
Point it at a directory of router configs. It builds the forwarding tables for every device, runs your reachability query, and tells you the answer, in under a second. Ships as a single binary. Nothing else to install.
A demo for the engineer, an overview for the executive, and a walkthrough of the command line. The terminals show real output from the tool.
For the engineer holding the change window.
A three-line OSPF change that passed peer review, shown twice: pushed straight to the network, then checked with Hammerhead first.
The labs are synthetic and small. The push at 01:48 is a labelled dramatization of what the model says would happen. The Rogers 2022 segment is a reconstruction from the public record; the demo does not claim Hammerhead would have prevented that outage.
For the executive who signs off on the risk.
A diff shows what was typed, not what the network does next. Where a pre-change gate fits, without moving the approval chain you already run.
The two incidents are cited from the providers' own reports as examples of change risk. The video does not claim Hammerhead would have prevented them, or that AI caused them. The terminal shows a small synthetic lab.
For the engineer at the keyboard.
One command per chapter, typed and run: what it found in a folder of configs, what it could not read, and what a change does.
Every chapter runs on the small synthetic labs that ship with Hammerhead. The output is real: colour is added, and long output is clipped or excerpted, never edited.
Nothing in these videos was pushed to a production network. Narration is a synthetic voice; English captions are in each player.
We rebuilt the change behind 134 publicly documented network outages and ran each through Hammerhead. It flags every one for its cause: 133 from the configuration change, and Microsoft’s 2023 WAN outage from the command that was run. Microsoft never published the vendor or the command, so for that one both are our assumption.
Reconstructions from public reports, not the operators’ own configurations. Flagging the cause is not a claim that any outage would have been prevented.
Read raw configs, run protocol convergence, build the routing and forwarding tables.
Ask where a packet goes. Reachability, traceroutes, path joins, IP ownership.
Diff snapshots, detect loops, scan for single points of failure, audit ACLs.
Check configs against a YAML compliance DSL. CIS, PCI, and SOC 2 templates included.
Single static binary. No Docker, no JVM, no server.
Notebook-native. from hammerhead import Hammerhead
An axum server with 11 endpoints for wiring into anything.
Gate merges on a FIB diff. Fast enough to run on every commit.
8 tutorial notebooks: BGP analysis, traceroute, change validation, ACL walkthroughs.
Matches industry-standard analysis at 99.93%, 800× faster, fully deterministic and diffable.
Finds the fault, writes the exact CLI patch, and proves it restores reachability before you approve it. In seconds. On your own hardware.
The slow part of an incident was never the fix. It was finding the fault and trusting the repair. Config Studio does both, and proves it, before you approve.
A chat wired to 15 network tools and an in-session config editor. Ask in plain English; it reasons over your fabric and proposes verified edits inline.
A webhook receiver that runs diagnose → patch → verify on every commit, posts a verdict comment with a deep link, and can gate the merge.
Paste your config, get a full report. Shadowed rules, overly permissive access, compliance gaps. No sign-up, no install, runs in your browser.
Rules that never fire because a broader rule matches first.
Wide source and destination ranges, any-any patterns.
Duplicates that add complexity without changing policy.
First-match semantics producing unintended outcomes.
Missing deny-all defaults and logging gaps.
Zero-hit candidates for cleanup.
Start free and verify a change today. Add your team when you're ready, and your org when you need AI remediation and air-gap.
For the engineer getting started with verified change.
For the engineer who ships changes daily.
For teams gating change together.
For orgs that need AI remediation and air-gap.
Every tier runs on your own hardware. Your configs never leave your network — on any plan.
Questions about Optimesh, your network, or partnering with us? Reach out and you'll get a real person on the founding team, usually within a business day.
Bring one recurring network incident. We'll diagnose it, patch it, and prove the fix — on your configs, in your environment.
Deterministic verification for every AI-driven infrastructure change.