Your agents keep rebuilding context. Myelin stops the waste.
Myelin keeps the working state behind long-running agents alive across sessions, machines, model swaps, and handoffs. The next session starts with the files, decisions, and constraints already understood. Your team gets more completed work with fewer repeated turns and less token overhead.
Working context resumed instead of rebuilt.
Long runs became practical for our own team.
Production agent work run by Granica on Myelin.
Granica internal production usage.
Every session starts smarter.
Myelin keeps the working intelligence built during a coding session and carries it into the next one. The agent spends less time rebuilding context and more time moving the work forward.
- Files read
- Decisions made
- Constraints found
- Failed paths
- Less re-reading
- Fewer repeated turns
- Lower cost per accepted task
How it works
Myelin records what the session read, built, and decided. It uses that working state to manage context, cache reuse, and model selection on the next request.
The intelligence layer in the request path.
Myelin sits beneath supported agents and above the model APIs. It remembers working state across turns, manages context and cache shape with that state in view, and records every run.
- One config change, instant rollback
- Context, caching, and model selection share one working state
- Intent, model, cost, and outcome recorded for every run
POST /v1/messages → Anthropic
POST /v1/messages → Myelin → Anthropic
Three ways to run Myelin.
Choose who operates the control plane and where the data plane runs.
- 01
Managed Cloud application
- Control plane
- Granica
- Data plane
- Granica
The fastest path to start a pilot and evaluate Myelin on your own traffic.
- 02
Hybrid
- Control plane
- Granica
- Data plane
- Your cloud account
For teams with data-residency requirements. Currently validated on AWS.
- 03
Fully self-managed
- Control plane
- Your cloud account
- Data plane
- Your cloud account
Available for select strategic engagements that require full operational control.
The work moves with the team.
Beam it to another machine, switch supported agents, or hand it to a teammate. The working state stays with the session.
Work that runs for days, not hours.
Long-running coding sessions
As a coding session progresses, Myelin builds working intelligence from the turns and interactions: files read, decisions made, constraints, and paths that failed. That intelligence carries into the next session, so the agent begins with more of the work already understood. Customers see the effect in fewer turns to an accepted result and lower cost per accepted task.
Cross-agent workflows
Different agents are good at different work, but switching usually means abandoning everything the session knows. Myelin holds working state beneath the agent, so you can design with one supported agent and execute with another, mid-workflow, without a reset. The new agent picks up the same context: task history, constraints, decisions. You choose agents on merit instead of on the cost of starting over.
Shift-change handoffs
When a debugging session changes hands today, the code moves but the reasoning does not: the next engineer inherits the branch and none of the hypotheses, so the first hour is re-discovery. With Myelin the live session itself is the handoff. The next engineer resumes mid-task with every hypothesis, every dead end, and every decision intact, and the agent already knows the codebase and the constraints. The briefing becomes a sentence, not a meeting.
Batch run recovery
An overnight job fails at 3 a.m., partway through work you have already paid for. Rerunning from zero means paying twice for everything that succeeded before the failure. Myelin checkpoints session state as the run progresses, so recovery resumes from the last good state instead of from scratch. You pay for the failure once, not for the successes twice.
Side-by-side fix trials
When two fixes look equally plausible, the honest answer is to try both, but nobody wants to rebuild context twice. Myelin forks the live session, and the context the agent already built, the repository knowledge, the constraints, the failed attempts, carries into each branch. Both trials start warm. You compare real outcomes instead of arguing about hypotheticals, and keep the branch that wins.
Your state, not our training data.
What Myelin learns is state, not a model: your sessions' context, cache, and routing signals, stored per customer, isolated to your tenant, and used only to serve your own sessions. Nothing trains any model, ours or anyone else's.
Working state is isolated to your tenant.
State serves your traffic, not another customer's.
Your code, prompts, and state do not train a model.
Supported agents
Claude Code and Codex are supported. Other harnesses are validated case by case.
How it fits together
Myelin lowers the cost of the agent layer.
Myelin keeps working state alive so agents do not repeatedly pay to rediscover the same context. Lower in the stack, Crunch reduces the cost of storing, processing, and maintaining the enterprise data those AI systems depend on.
See how Crunch lowers data costsStart with one workflow. Prove it on your traffic.
We define the task, deployment model, and acceptance criteria with your team before the pilot begins.
- 01
Scope the pilot
One team, one long-running workflow, and clear acceptance criteria.
- 02
Choose deployment
Managed Cloud application, hybrid, or fully self-managed.
- 03
Measure the result
Quality first, followed by turns and cost per accepted task.
FAQs
What is Myelin?
Myelin is the intelligence layer between supported coding agents and model APIs. It carries working state across sessions, manages context and cache reuse, and records each run so teams can improve quality and cost per accepted task.
What does Myelin remember?
Myelin remembers the working state behind the task: context, files read, decisions made, constraints, session history, and work in progress. That state carries into the next session instead of being rebuilt from scratch.
Which agents do you support?
Myelin supports Claude Code and Codex. We validate other agent harnesses case by case.
How will we measure the impact?
Quality comes first. We measure the turns and cost required to reach an accepted task, then show context reuse, spend, and agent turns for your own traffic in the dashboard.
How do you handle our code, prompts, and working state?
Working state is kept per customer and isolated to your tenant. It is used only to serve your sessions. We do not train models on it, and there is no cross-customer sharing of your data.
How is Myelin deployed?
Choose the Managed Cloud application with both planes operated by Granica, hybrid with the control plane operated by Granica and the data plane in your cloud account, or fully self-managed with both planes in your cloud account.
What does the security review cover?
Security review is part of every pilot. We walk your team through the control matrix, data path, and deployment model before anything runs on real traffic.
How do we evaluate Myelin?
Bring a long-running coding workflow and run normal work through Myelin. We will compare quality, turns, and cost per accepted task on your own traffic. Book a demo to plan the evaluation with our team.