Can we run it inside our own network?

Yes. The router runs as a container or a Helm release on your infrastructure, and a routing rule keeps regulated data on the models you allow.

Will this lock us into another vendor?

No. The router is Apache-2.0 open source, your provider keys stay yours, and the API is OpenAI-compatible, so leaving is a change of base URL.

How much can we save on our LLM bill?

On the public benchmark the router saved 89% against sending everything to the reference model. Import last month's provider bill on the bill page and the estimate is computed on your own traffic before you change a line of code.

Legal · use case

Confidential documents, the strongest reasoning for them, and a person when the model is unsure.

Contracts and filings route to large-context, high-reasoning models; a confidence floor sends any low-certainty answer to counsel instead; data-boundary rules keep privileged documents off public endpoints; every decision is on the record for the matter file.

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Free plan, no card. Self-hosting is free forever; the rules below run the same way on both.

The situation

What the team is dealing with today

Legal work is long documents, high stakes and confidentiality. A cheap model misses a clause; a frontier model on every e-mail is wasteful; and the answer a lawyer must not rely on looks exactly like the one they can - unless the router says how sure it was and hands the doubtful ones to a person.

What changes

Contracts and long filings on large-context, high-reasoning models
Answers below the confidence floor routed to counsel, not returned as fact
Privileged documents kept inside the data boundary by policy

One request

What happens, step by step

Long contracts go to large-context models; a confidence floor routes low-certainty answers to counsel.

Contract arrives
Length and complexity measured
Large-context model answers
Confidence below the floor: counsel reviews
Decision logged

Route a request like this in the playground and read the trace

A legal request, quoted live“Review this indemnity clause and list the obligations it places on the supplier, with the risk each one carries for us.”

Quoting every candidate in the public catalogue...

The policy

Two text files, not a rewrite

This is the rules.yaml that produces the behaviour above; targets.yaml names the models, agents and people it refers to. The floor is one router setting: below min_confidence the request goes to fallback_target instead.

rules.yaml - legal (reference configuration)yaml

rules:
  - name: contracts-need-context
    when:
      domains: [legal]
      min_complexity: 0.5
    prefer: [llm-frontier]
    weight: 0.8

  - name: anything-doubtful-to-counsel
    when:
      domains: [legal]
      actions: [escalate]
    prefer: [counsel-review]
    pin: true

# router settings:
#   min_confidence: 0.55
#   fallback_target: counsel-review

Example: Illustrative configuration or synthetic data, not a customer's.A reference configuration to start from - rules the router enforces as written, not a description of how a named customer runs it.

Other use cases

For the business

What it does for the whole organisation.

Cloud, self-hosted or on-premises
Run it where the data is
The same router ships as a hosted platform, a container image and a Helm chart; the data boundary is a routing rule.
Deployment options
One URL, every vendor
No vendor lock-in
Point your OpenAI-compatible client at one address; add, swap or retire providers in the catalogue without touching application code.
Every vendor side by side
89% less
Lower cost per request
On the 150-prompt benchmark the router spent 89% less than sending every prompt to the reference model, and the judged quality went up, not down.
Read the benchmark

Can we run it inside our own network?: Yes. The router runs as a container or a Helm release on your infrastructure, and a routing rule keeps regulated data on the models you allow.
Will this lock us into another vendor?: No. The router is Apache-2.0 open source, your provider keys stay yours, and the API is OpenAI-compatible, so leaving is a change of base URL.
How much can we save on our LLM bill?: On the public benchmark the router saved 89% against sending everything to the reference model. Import last month's provider bill on the bill page and the estimate is computed on your own traffic before you change a line of code.

Start with the legal rules and change what you disagree with.

OpenSmartRoute is open source and the free plan keeps the full trace of every decision. Create a workspace, paste the rules, route a request.

Create a free account Read the benchmark

Free plan, no card. Fifteen thousand decisions a month with the full trace.

rules: - name: contracts-need-context when: domains: [legal] min_complexity: 0.5 prefer: [llm-frontier] weight: 0.8 - name: anything-doubtful-to-counsel when: domains: [legal] actions: [escalate] prefer: [counsel-review] pin: true # router settings: # min_confidence: 0.55 # fallback_target: counsel-review

Confidential documents, the strongest reasoning for them, and a person when the model is unsure.

What the team is dealing with today

What happens, step by step

Two text files, not a rewrite

What it does for the whole organisation.

Run it where the data is

No vendor lock-in

Lower cost per request

Start with the legal rules and change what you disagree with.

Confidential documents, the strongest reasoning for them, and a person when the model is unsure.

What the team is dealing with today

What happens, step by step

Two text files, not a rewrite

What it does for the whole organisation.

Run it where the data is

No vendor lock-in

Lower cost per request

Start with the legal rules and change what you disagree with.