The enterprise coding agent
mo connects your engineers to every approved model, frontier and open-weight, through a single gateway and execution harness. It speeds developer workflows, cuts spend with automated task-to-model routing, and gives leadership one control plane for usage, cost, and policy.
brew install momentohq/tap/momo login. macOS and Linux only for now.
Benchmarks
Real benchmark results from 6 production repos containing real tasks, scored by an independent multi-model judge panel.
indexed to Claude Opus 4.8 = 1.0×
shorter is cheaper
mean score on a 0 to 5 scale
both passed 6/6 automated suites
The harness matters too: on the same model, native mo ran up to 4× cheaper and ~2× faster than Claude Code, with no measurable quality difference.
Want to evaluate your own models? The same harness powers our enablement workflow: evals built on your tasks, run in your perimeter, repeatable results with each new model release.
Bring your own agent
mo launches the harness you already use, unchanged, through the gateway, with model choice, budgets, and zero data retention included.
mo ccClaude Code, zero-data-retention pipemo piPi, zero-data-retention pipePrivacy
mo's gateway retains no prompt, code, or reply content. What it keeps is a metadata-only usage record.
Zero data retention is enforced in the gateway, on every request. Beyond the gateway, a request reaches only the provider you chose, and per-key route restrictions keep teams on approved providers.
Enterprise governance
Budgets
Per-user daily/monthly ceilings. Hard 402 at the limit; every response carries available usage in a header.
Keys
Mint, scope, revoke in seconds. Virtual keys restrictable per model route. No redeploys.
Metering
Every request, one record, errors included, rolled up per user, team, org, and project. Optional SSO dashboard.
Permissions
Plan & Build modes. Agents stay read-only until the developer approves; ambiguous commands are blocked by a model-backed safety judge instead of guessing; hard-deny rules ship built in and no local config can override them.
Sharing
/grant a live session to a named teammate. Time-limited by default, visible to the owner, revoked with one command — and credentials never leave the gateway.
Remote
Approve from your phone. Watch, prompt, and approve or deny gated actions from a paired mobile client.
Compare
| mo | Pi (open source) | Claude Code | |
|---|---|---|---|
| Permission system | Plan & Build modes, model-backed safety judge, configurable allow/ask/deny tiers | None built-in; runs with your full user permissions | Per-action approvals and allowlists |
| Where your code travels | Through a zero-data-retention gateway; records are metadata-only | Straight to each model provider, on your own keys | To the model provider, per its data policies |
| Models | Frontier and open (Claude, GPT-5.5, GLM-5.2, DeepSeek), one string to switch | Multi-provider, bring your own keys | Claude models |
| Automatic model routing | Phase shift: hard reasoning on a frontier model, routine work on an open model, automatically | None | Plan-vs-execute split, Claude models only |
| Budgets & metering | Per-user ceilings with hard stops; rollups per user, team, org, and project | None | Varies by plan |
| Team visibility | Session sharing, live metadata tail, phone-based remote approvals | None | Varies by plan |
| Runs other harnesses | Yes: mo cc and mo pi route them through the same gateway |
None | None |
Scope: coding-agent harnesses (the tools a team would otherwise standardize on), not general LLM gateways or IDE assistants. Based on public documentation, July 2026. Pi is a minimal harness and does that job well. mo exists for teams that need the enterprise layer around one: privacy, budgets, and visibility.
Enablement
Moving real coding volume to open-weight models is an engineering decision, and it needs data. Momento runs embedded enablement engagements that give your platform team the data to make the call, and the tooling to retest every time a new model ships.
Evals
A benchmark suite for your workloads. Built on the tasks your teams run (code review, bug fixes, migrations, incident triage), scored against the frontier baselines you already pay for, with an LLM judge that's validated against human-labeled samples before its grades are trusted. Verifiable against every new model release.
Bake-offs
Providers, measured on your workload. The managed inference providers serving your shortlisted models, raced head-to-head: time-to-first-token, p95/p99 latency, sustained throughput under concurrency, availability, consistency, and price. The winner is wired into your gateway routing, and the race reruns as providers evolve — so your deployment keeps improving instead of going stale.
Self-hosting
Open-weight models on your hardware. Open-weight models stood up on your own hardware (vLLM/SGLang, FP8/FP4), behind your gateway, inside your perimeter. Measured against the managed options down to break-even volume, and handed off as reusable Terraform.
Delivered as embedded sprints with your engineers: architecture deep-dives (mixture-of-experts, attention and KV-cache design), provider landscape briefings, and a full handoff, so your team can re-run everything without us. Ask about an enablement engagement
Security
The team that runs serverless infrastructure for enterprises in production; the gateway runs on that same platform. The pieces a reviewer usually checks: zero data retention, allow-listed egress, fail-closed auth.
Keep it. The anthropic/ route is a transparent passthrough: bring your own key under your existing terms; mo adds metering and harness guardrails around it.
Access rides on revocable keys, re-read on every request, so revocation takes effect immediately and needs no redeploy. A session token already issued to that developer keeps working until it expires, up to an hour.
macOS and Linux via Homebrew today. Usage is metered per request with budget ceilings on top; commercial terms: hello@momentohq.com.
Get started
brew install momentohq/tap/moThen run mo login and pick a model.