CASCADE DYNAMICS
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ONE COORDINATION LAYER FOR EVERY KIND OF AGENT · EARLY BETA

Many agents. One plan. No collisions.

Coding agents sharing a repo. AI swarms working toward a goal. Drones, humanoids and robot fleets sharing space. Before any of them acts on something shared, it asks Cascade. One gets it, the others are told who has it and move on, and every decision gets a receipt anyone can check.

Coding agents Agent swarms Drone fleets Humanoids & robots
Get a free API key → Coding agents: 2-minute file-lock hook
Building with AI? Paste this into any AI tool — Codex, Claude Code, Cursor, Grok, Lovable and more: Read cascadedynamics.ai/SKILL.md and show me where Cascade fits across all my projects
SIMULATED RUN 4c81-9f · orchard-survey
simulated demo run · anyone can verify
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SIGNED DECISIONS
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DUPLICATE GRANTS
0
DUPLICATES
0
TOKENS SPENT
LATEST RECEIPT
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LIVE · PRODUCTION LEDGER
DECISION STREAM
THE FILE-LOCK HOOK

Two agents open the same file. Only one gets to write.

Without it, the second write silently wipes the first. The hook is one small file. It runs before every edit and needs no change to how you prompt.

01 · ASK FIRST
The hook claims the file before each edit.
Claude Code, Codex and Cursor all run it through their own hook settings.
02 · ONE WRITER
If another session has it, the edit is refused.
The agent is told who holds the file, so it works on something else.
03 · HAND BACK
Files are released when the turn ends.
A crashed session's hold times out. If the API is down, edits go ahead with a warning.
04 · RECEIPTS
Every grant and hold is signed.
You can show which session had which file, and check it offline.

Tested with each tool's documented hook format: 13 of 13 cases, including a crashed session and the API being down. Free to start: 1,000 decisions before you verify your email, 1,000,000 after.

Set up the hook Read the hook source

The future is already here, and it moves faster than anyone can watch. When thousands of agents act at once, “what happened?” needs an answer you can prove — to your team, your customers and your auditors. You can’t afford to run them blind.

Your models decide what to do. Cascade decides who does it, across the whole fleet as it happens, and signs every decision so anyone can check how and why — without having to trust us. Receipts check out fully offline, and on-prem, air-gapped deployment for the field is coming soon. Scale you can stand behind: the responsible next step for autonomous AI.

WORKS WITH EVERY FRONTIER MODEL YOU RUN
Your models decide what to do. Cascade is the layer beneath them that decides who does it — no model in the decision path, so it works the same whichever one you run.
WHERE IT FITS

Your stack runs your models. Nothing runs the fleet.

Keep the tools and the model you use. Cascade adds the layer they leave out: coordinating every agent at scale, and a record of every decision you can inspect and prove.

LLM GATEWAYS
Route and rate-limit model calls.
Don’t decide which agent gets the job.
GUARDRAILS
Filter what a model says.
Don’t stop two agents taking the same task.
OBSERVABILITY
Log what happened, afterwards.
Can’t prevent it, or prove the log wasn’t edited.
AGENT FRAMEWORKS
Plan the work and run the agents.
Coordinate only inside their own run, and their logs can be edited.
CASCADE
Coordinates every agent and system, at scale.
Decides who acts before they act and signs every decision, so it checks out even offline. No tokens per decision.
SWARMS TOWARD A GOAL

Point a swarm at a goal. Let it find the way.

Give your agents one goal and a way to check it. Each agent picks a task, does it, and adds what it learned as new tasks, so the plan grows while they work. Cascade is the referee underneath: one agent per task, one writer on the plan at a time, and a signed receipt for every handoff. Any model, any agent framework, no extra tokens.

01 · GOAL
Say what done looks like.
Tests pass, a number is reached, a question is answered. The swarm stops on proof, not on an agent saying so.
02 · SPREAD OUT
Every agent asks before it starts.
If a task is taken, the agent is told who has it and picks another. No two agents work the same task at once.
03 · LEARN AND ADD
The plan grows as they learn.
Each finished task can add new ones. If an agent crashes, its task frees up and another agent takes it.
04 · PROVE IT
Every step has a receipt.
Each task records which agent did it and the signed decision that let it. Anyone can check the record offline.

Tested on our machine, 2026-10-19: 6 agents, a 40-task goal, one agent killed mid-task in every run. 5 of 5 runs reached the goal in about 4–5 s, each task done once, 0 double holds.

Give SKILL.md to your AI tool Get the swarm loop More recipes: file locks, never twice, limits →
01 — THE PROBLEM

More agents. More speed. Less idea what happened.

Every fleet hits the same wall. Agents reach for the same task, the same airspace, the same ticket — and afterwards nobody can say who decided what, or why. You can ask an AI model to referee: pay for every call, wait on it, and get a different answer next time. Or you can put a referee there that never guesses.

ASK A MODEL TO DECIDE
    PUT CASCADE THERE

      Your AI model is great at deciding what to do. It is the wrong tool for deciding who gets to do it. Cascade does only that part.

      02 — TWO WORLDS, ONE LAYER

      Things with mass. Things without. Both need a referee.

      One API and one trail of receipts for both. The difference is only what a mistake costs you.

      TRACK 01 — BODIES

      In the physical world, mistakes are permanent.

      Humanoids, drone swarms, robotaxis, warehouse fleets, field robots, satellites, defense systems. When two of them want the same space, the decision has to be right the first time — and provable afterward.

      TRACK 02 — AGENTS

      Duplicated work is invisible.

      Planners, tool swarms, game AI, simulations. Nothing crashes — you just pay twice, three times, for the same result, and never find out where it went.

      TRACK 03 — ?

      One API, both tracks. Which means the third is whatever you point it at — swarm simulation, market making, a thousand NPCs sharing one world state. Go find out.

      03 — WATCH IT DECIDE

      Watch every decision get its receipt.

      Each dot on the ring is an agent. When one is given a job, a line is drawn; the moment it is decided, the decision is signed and a tick lands on the edge. What you are watching is the audit trail being written — there is no second system recording it later.

      LIVE DECISIONS
      —
      — job given| tick = signed receipt● idle
      04 — THE PROOF

      Don't take our word for it. Check the receipt.

      Four checks run on your own machine, offline, against our published public key. Flip the switch and we change one byte of one decision — then watch the checks catch it.

      VERIFICATION — RUN 4c81-9f · 14,208 ENTRIES
      Verified — 4 / 4
      TAMPER WITH IT
      entry 1entry 14,208
      WHAT IF THIS WERE ALTERED?
      Flip the switch. We alter a single byte of one decision and re-run the same four checks in front of you.
      Export bundle Public link
      TESTED IN PUBLIC — DABSTEP BENCHMARK
      We ran governed agents through Adyen's public 450-task benchmark, eight officially graded entries in four days: final entry 92.22% overall — first among credible entries on every axis, an arc of 39.95 → 91.01 on hard tasks with the last four entries at ~$0 marginal model spend, 900/900 signed coordination claims, and zero human minutes mid-run. Every score published, including the regressions — methodology disclosed.
      See the numbers →
      05 — FOR DEVELOPERS

      Ten lines. One afternoon.

      One call to ask for a job, one to hand it back. If another agent already has it, you are told to wait — no race. Every decision is recorded automatically, and your bill is counted from the same signed record.

      Get a free API key Read the docs
      key pre-filled
      
            
      → 200 · granted · signed 0x7f3c…d044
      0 tokens · 0.4 ms decision compute
      06 — ORBIT, DEFENSE & CRITICAL INFRASTRUCTURE

      Receipts that check out with no network. Holds up in review.

      No model in the loop, and an after-action certificate that verifies on an air-gapped laptop with nothing but our public key — that works today. Full on-prem, disconnected deployment, with nothing leaving your perimeter, is coming soon.

      Two spacecraft must never book the same ground station at the same moment, and no operator wants to discover that conflict from the telemetry afterwards — so Cascade decides it up front, and signs what it decided.

      07 — PRICING

      Start free. Go to production for $49.

      1,000,000 free decisions, no cardTop-ups: $10 per 250,000 · never expire

      Start on the free beta. Upgrade to Builder when you go to production, or add top-ups when you need more. Cancel anytime. Your bill is counted from the same signed record as your receipts, so you can check every invoice yourself.

      ESTIMATE YOUR VOLUME · FIND YOUR TIER
      AGENTS · 1
      DECISIONS PER AGENT / HOUR · 1
      SIGNED DECISIONS / MONTH
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      RECOMMENDED TIER
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      FREE BETA AND BUILDER ARE LIVE · TEAM COMING SOON
      Estimate: agents running around the clock; each decision would take about 600 LLM tokens if a model refereed it, priced at $3 per million tokens. Cascade spends no tokens.
      ON-PREM, DEFENSE & PARTNERSHIPS
      Fleets beyond 25M decisions a month, on-prem and air-gapped deployments (coming soon), integrations and reseller partnerships. Tell us what you are building.
      Talk to us →

      Start free. Prove everything.

      Free API key, public beta, no sales call. Try tampering with a receipt and see if we catch it.

      Get a free API key Talk to us about on-prem
      © 2026 Cascade Dynamicscascadedynamics.ai