Entelligence sits in front of other agents.ML.ai Code writes the code itself.
Two different things: a coding agent versus a router-and-review layer for agents it doesn’t build. Pick ML.ai Code for one agent, one login, no separate provider key. Pick Entelligence for visible, tunable routing in front of a coding agent you already have.
What each one actually is
ML.ai Code reads your repo and writes the edit itself, gated by an Allow/Always/Deny prompt before anything touches disk, with commands classified by effect before they run. One login, no separate provider key to obtain or pay for. Its built-in `/review` command can also review a diff, commit, branch, or PR by URL, cross-repo, on demand. ML.ai Inference behind it routes to one of two tiers, Standard or High, without naming the model.
A Model Router that classifies each turn in under 50ms, picks Balanced or Eco routing, pins the model for the session, and escalates to a stronger one when a turn needs it, self-hosted or on your own provider keys. Alongside it: a PR-review bot that comments automatically once a pull request opens, and an IDE extension that surfaces the same review inline. None of it writes code; Claude Code, Codex, or Copilot still does that underneath.
Same request, two receipts: watch what each router actually tells you.
Entelligence’s router names the model it picked and what that turn cost. ML.ai Inference reports a tier and a bill; which model served the request isn’t exposed.
Same request, two receipts
“Refactor this handler”
Entelligence Router
Entelligence names the model and cost for every turn. ML.ai reports a tier and a bill; the model itself isn’t exposed.
Which one do you actually need?
Use this if
You want one vendor for the whole job, writing the code and running it, with a single login and no separate provider key to manage, and every change stopped and shown to you before it touches disk.
Use this if
You already have a coding agent doing the writing and want a layer on top of it, one that lets you see and tune the routing policy yourself, or reviews every pull request automatically without anyone having to ask.
Every claim, side by side
The same categories, compared row by row. Every line on both sides traces back to a real doc, pricing page, or published benchmark.
vsWhat it is
What it actually is
A Model Router with visible policies, plus a separate PR-review bot and codebase-chat layer ("Ask Ellie").
A coding agent that writes code
No coding agent of their own. Their IDE extension reviews and comments; code generation still comes from Claude Code, Codex, or Copilot.
How it works
Routing control
User-selectable Balanced (favor quality) or Eco (favor lower cost) policy.
Routing mechanics
On-box classification claimed under 50ms per turn, with escalation to a stronger model when a turn needs it.
Cost visibility
A per-turn cost log with real spend shown per request.
Deployment / keys
Self-hosted or BYOK, your own cloud and keys, on top of whatever Entelligence itself bills.
PR / diff review
An always-on bot that comments the moment a PR opens, citing a self-published 47.2% F1 score on an 8-tool, 67-bug benchmark.
Change safety before it ships
No equivalent. Entelligence acts on code that already exists, with no pre-write gate of its own.
Compliance & pricing
Pricing transparency
No public plan sheet. Billing runs on a wallet balance (Proxy) or your own keys (BYOK).
Compliance disclosure
SOC 2 Type II, stated as a credential badge on their site.
| | |
|---|---|---|
| What it is | ||
| What it actually is | A closed routing harness. Requests go to ML.ai Standard or ML.ai High; the model behind each tier isn’t named. | A Model Router with visible policies, plus a separate PR-review bot and codebase-chat layer ("Ask Ellie"). |
| A coding agent that writes code | ML.ai Code reads your repo and applies edits and shell commands itself, once approved, in VS Code or Cursor. | No coding agent of their own. Their IDE extension reviews and comments; code generation still comes from Claude Code, Codex, or Copilot. |
| How it works | ||
| Routing control | None exposed. Two tiers only; ML.ai’s own docs call the routing behind each tier its decision, not yours. | User-selectable Balanced (favor quality) or Eco (favor lower cost) policy. |
| Routing mechanics | Not documented beyond the two-tier split. No published latency or classification figures. | On-box classification claimed under 50ms per turn, with escalation to a stronger model when a turn needs it. |
| Cost visibility | A tier name and a bill. No per-request or per-model spend breakdown. | A per-turn cost log with real spend shown per request. |
| Deployment / keys | Sign in with an ML.ai access token, nothing else. No self-hosted option today. | Self-hosted or BYOK, your own cloud and keys, on top of whatever Entelligence itself bills. |
| PR / diff review | A built-in `/review` command: full files and traced callers, not just the diff. Invoked on demand. | An always-on bot that comments the moment a PR opens, citing a self-published 47.2% F1 score on an 8-tool, 67-bug benchmark. |
| Change safety before it ships | Every edit and command is a real diff, held behind an Allow/Always/Deny gate before it touches disk. | No equivalent. Entelligence acts on code that already exists, with no pre-write gate of its own. |
| Compliance & pricing | ||
| Pricing transparency | A published plan table, five tiers, free trial to Enterprise, rates you can read before signing up. | No public plan sheet. Billing runs on a wallet balance (Proxy) or your own keys (BYOK). |
| Compliance disclosure | SOC 2 Type II, ISO 27001, and GDPR + CCPA, each published on ML.ai’s own security page. | SOC 2 Type II, stated as a credential badge on their site. |
Where each one actually falls short
ML.ai’s own limits get the same weight as theirs, not a footnote after the sales pitch.
Where Entelligence.ai is limited
No coding agent of their own; code generation still runs on Claude Code, Codex, or Copilot, each billed separately.
Router pricing isn’t a plan sheet; it’s wallet balance or your own keys, on top of whatever the underlying agent costs.
The 64% savings figure is one illustrative scenario, not a disclosed benchmark across team sizes.
The PR-review benchmark (47.2% F1, 8 tools, 67 bugs) is self-published; named competitors aren’t disclosed.
Where ML.ai is limited
ML.ai Inference’s routing is a closed two-tier system: no policy choice, no per-model cost log.
No self-hosted or BYOK option for ML.ai Inference; it’s fully managed only.
ML.ai Code’s `/review` has to be invoked; it doesn’t watch a repo and comment automatically like Entelligence’s bot.
Questions worth asking
Try ML.ai Code today, or talk to us about what is next.
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