The best model keeps changing
Frontier and open-source models leapfrog each other faster than any company can re-platform. Betting on one vendor is a bet you keep re-losing.
The model layer
Switch AI models freely — without losing what it knows.
The secure, efficient way to put every AI model to work. Swap models safely, keep every bit of context, and control every dollar of spend — CarveAI sits between your company and the model market, governed, auditable, and model-agnostic.
Any model
Your context, kept
One bill
Model for this task
SWAPPABLE
Claude today, another model tomorrow — the router picks per task. Your company's context comes along either way.
THE RECORD · append-onlylive
HITL Your approval needed
The research assistant wants to share 2 memories with the legal assistant.
The problem
The model market moves faster
The model market moves faster
than enterprises can react.
Context is the lock-in
Everything your company has taught its AI lives in prompts and histories tied to one model. Swap the model, lose the knowledge.
Runaway, unmanaged cost
Every task runs on an expensive frontier model whether it needs one or not, and teams stack subscriptions with every provider.
New models can't be trusted blind
Dropping an unproven or open-source model into production without guardrails is a sign-off no one wants to give.
The result: enterprises stay locked in, overpay, and fall behind the frontier.
Why we're different
Your context lives in the layer — not the model.
Everything your company teaches its AI — every private memory and the shared company brain — lives in CarveAI, not inside any one model. So what your company knows travels to whichever model runs next. Switching is a dropdown, not a migration.
Your company brainsmarter with every use
Overview
Policies
How we work
Security
Product
The solution
Your context, any model, one bill.
A secure, efficient way to reach every model: the router picks the right one, your context stays put, and every action is governed and on the record.
One router, 30+ models
Picks the best model for each task on quality, cost, and security.
Claude
GPT
Llama
tuned for you
Your context, portable
Memory lives in the layer, so switching models never loses what your company knows.
SHARED
PRIVATE
VAULT
You choose the model pool
Include or dismiss open-source models by policy — per agent or company-wide.
Governed & on the record
A human approves anything shared; every action lands in an append-only record.
How it works
Four steps from model lock-in to model freedom.
STEP 01
Connect
Plug into the systems you already use — Slack, email, docs, GitHub, databases.
STEP 02
Learn
Your company's context accrues in the layer — private memories, workflows, a shared company brain.
STEP 03
Route
From a catalog of 30+ frontier and open-source models, the choice is weighed on quality, cost, and security for the task.
STEP 04
On the record
Anything sensitive waits for human sign-off, and every step lands in an append-only audit log.
connected
SlackEmailGoogleGitHubNotionPostgres
How we price renewalsPRIVATE
Learned from your docs and past work — stored in the layer, not the model.
Task · summarize a contractROUTED
The router weighs quality, cost, and security, then picks the model that fits.
frontierchosen · tuned for youopen-source
THE RECORDcomplete
10:02:14MODEL_ROUTED#4821
10:04:38HUMAN_APPROVAL#4822
10:05:02DELIVERY_ACCEPTED#4823
0
frontier & open-source models
0%
of actions on the record
0
of your data used to train public models
0
bill for every model, not one per provider
The platform
A working product, and the full model layer around it.
Everything below runs today on AWS and Kubernetes.
A working product
Live on AWS and Kubernetes, built on LangGraph. A catalog of 30+ frontier and open-source models running on AWS Bedrock, personal and specialist agents, a shared memory system, an engineer dashboard, and full audit trails. Shipped and running in production, with enterprise deployments and pilots underway.
BoxGitHubGoogleMicrosoftNotionPostgreSQLSlack
The full model layer
Automatic per-task routing across the whole catalog, company-specific fine-tuned models, and repetitive workflows turned into deterministic endpoints.
Carve Protect
And it's all trusted, on the record
Your data
- Kept separate, encrypted, never used to train public models
Memory
- Private by default, shared only on approval
Assistants
- A person approves anything shared
- Each sticks to its own job
Book a demo
See your context outlive any model.
A 30-minute walkthrough on a workflow your team actually runs.