Loom keeps your agents on track.

You tell Loom once, all your agents recall at the right time.

For developers and teams using Claude Code, Codex, or OpenCode on work that spans more than one session.

Your coding agent can be brilliant—and still forget what made it effective. Context compaction or a closed session can wipe out hours of explanation, so the next task starts without the decisions, constraints, and hard-won lessons that kept the work on track. You have to repeat yourself, maintain exhaustive docs, and write detailed instructions for every small change just to keep your agents on track. Before long, you become your agents' long-term memory and guardrail.

Loom frees you from the exhausting job of babysitting your agents. It gives every agent one shared, durable memory across sessions, tools, and machines. Tell Loom once, and it brings back the right instructions, decisions, and context just before an agent acts—not buried in a document it may never read. Your agents stay aligned, make better decisions, and move faster with fewer prompts and fewer wasted tokens.

A real example: record why your team rejected a database migration today; when another agent plans related work next week, Loom returns that decision and its reasoning before the agent proposes the same migration again.

Get started See it in action

Free hosted plan · hosted store data encrypted at rest and in transit.

Loom Cloud is in a limited public test: the number of accounts is capped, and sign-up pauses when the test is full.

Why Loom

Build memory that compounds

What one agent learns becomes current knowledge every authorized agent can use—without starting from zero or repeating the same instructions.

Durable knowledge, not chat history

Loom preserves decisions, constraints, and discoveries as knowledge agents can reliably reuse—not a transcript they must reread from the beginning.

One shared memory for every agent

Every authorized agent can build on the same current knowledge across sessions, machines, operating systems, and coding tools.

The right context before action

Loom brings back the relevant decisions, constraints, and hard-won context just before an agent acts.

Control that fits your team

Use Loom as a hosted service or deploy it in your own infrastructure, with the security, control, and compliance model your team requires.

Multi-agent coordination

Keep every agent moving

Set a goal and permissions, and Loom gives your agents one shared place to organize tasks, claim ownership, coordinate handoffs, and continue work across sessions, repositories, and machines.

Institutional knowledge

Turn team knowledge into coordinated action

Each Loom store preserves a team’s knowledge, working principles, and boundaries. One agent can connect to multiple stores, so it can work across teams with the right context for each one—following local rules without mixing everything into one giant pool.

Coordinate across teams Authorized agents can publish, claim, revise, and complete shared work without turning a developer into the relay between them.
Combine specialist agents A coding agent implements the change, a QA agent checks it, a deploy agent releases it, and a support agent turns customer evidence into safe follow-up work.
Keep knowledge within team boundaries Development, QA, deployment, and support agents contribute where they own work, use authorized evidence, and avoid unrelated or restricted context.
Continue across sessions and machines When one session or machine stops, another agent can continue from the saved task state and handoff—without waiting for a developer to reconstruct the context.
Shared work, protected knowledge Coordinated in real time
Distributed agents coordinate work while respecting team knowledge boundaries Codex, Claude, and OpenCode run on different operating systems with dev, QA, deploy, and support roles. They coordinate through one shared work board while each team controls access to its own Loom store. Agents on real machines Team knowledge stores work work work work edit edit edit edit read read read
Codex / Linux
Dev agent
Implements, builds, and leaves the change evidence.
Codex / Windows
QA agent
Runs browser and OS checks where failures happen.
Claude / macOS
Deploy agent
Promotes a reviewed build and records live health.
OpenCode / Linux
Support agent
Reads private customer evidence and files sanitized follow-ups.
 Shared work board
Claim
owners
Done
evidence
store
coding
dev edits
QA reads
store
qa
QA edits
deploy reads
store
release
deploy edits
support reads
production
customer
support only
In practice: one agent’s result becomes the next agent’s trusted starting point. Each team keeps control of its knowledge while authorized agents carry work across the organization without losing context.
See it in action

See how Loom changes agent work

Compare the same work without Loom’s shared memory and with the right context already available.

1Turn scattered facts into reliable knowledge
Without Loom
Alex running Claude on Linux
--- user input --- As of April 1, 2026, we pay $340/mo for AWS, $120/mo for OpenAI, and $60/mo for Cursor. --- agent action --- the numbers live in this chat thread only
Alice running Codex on macOS (weeks later)
--- user input --- What's our total monthly spend on paid tools? --- agent action --- searches old chats for numbers mentioned once, months apart, with no single place holding the current numbers --- agent output --- I found some of these mentioned before, but I can't be sure the amounts are still current. The right information stays buried in a haystack
With Loom
Alex running Claude on Linux
--- user input --- As of April 1, 2026, we pay $340/mo for AWS, $120/mo for OpenAI, and $60/mo for Cursor. --- agent action --- organizes each service as a current, reusable record
Paid services · current as of 2026-04-01
ServiceMonthly cost
AWS$340
OpenAI$120
Cursor$60
Alice running Codex on macOS (weeks later)
--- user input --- What's our total monthly spend on paid tools? --- agent action --- reads the current records and returns the exact total --- agent output --- $520/month, across 3 services. Organized data turns memory into an asset
1 / 7
Benchmarks

Validate Loom on real memory benchmarks

Loom reports results from disclosed cohorts of three major AI memory benchmarks alongside clearly labeled same-cohort or published-paper reference points. Together, they test whether memory stays current, survives long histories, and supports real agent work. Loom also cuts measured token spend for agents that use it — see the token-savings study (PDF).

STALE
Consistency
86.1%

Tests whether memory recognizes superseded facts and adapts when new information changes what is true. On the same disclosed 141-scenario cohort, the CUPMem reference run scored 78.7%.

Benchmark details
LongMemEval
Recall
89.3%

Tests recall and reasoning across long, multi-session histories, including temporal questions and knowledge updates. GPT-4o full-context: 60.6%.

Benchmark details
AMA-Bench
Trajectories
75.6%

Tests memory over agent actions, tool outputs, state changes, and outcomes across realistic tasks. For context, the AMA-Bench paper reports GPT-5.2 full-context at 72.3%; cohorts and model backbones differ.

Benchmark details

Loom figures reflect 141 of 400 STALE scenarios, 149 LongMemEval questions, and 43 of 208 AMA-Bench cases. See the benchmark details and partial reproducibility receipt. STALE comparison figures are same-cohort reruns; LongMemEval and AMA-Bench references are published paper figures (STALE paper: Chao et al., arXiv:2605.06527 · LongMemEval: Wu et al., arXiv:2410.10813 · AMA-Bench: arXiv:2602.22769, ICML 2026).

Install

Start in minutes

Connect Loom and give your coding agents a shared memory in two steps.

1

Install the Loom CLI

One OS-specific command installs a stable, per-user loom command. No coding agent and no signed-in account required yet.

2

Run loom setup

One command finds the coding agents already on your machine—Claude Code, Codex, and OpenCode—connects your hosted store, and configures each one it finds. Nothing to hand-edit, nothing to repeat per agent.

Pricing

No per-seat or per-agent fees

Use hosted Loom free, or run Loom on your own server with a private install. Neither plan charges per seat or per agent, so adding developers or agents does not raise the bill by itself.

Hosted
Free
  • 5 managed cloud stores, 200 MB total storage
  • No per-agent limits
  • Email support
  • Encrypted at rest
Get started
Private install
Contact us
  • Run Loom on a server you operate
  • The same Loom as the hosted plan
  • Your stores and data stay on your server
  • No per-seat or per-agent charges
  • Licensed per server, per year
Contact us
Get started with Loom

Put Loom to work

Create your stores, connect your coding agents, and stop rebuilding context from scratch.

Get started

Create your stores and get a ready-to-paste connection bundle.

Loom Cloud is in a limited public test: the number of accounts is capped, and sign-up pauses when the test is full.