Switch AI models safely.
Cut the cost.

ACSI tests cheaper models on your real workloads, repairs the prompts needed to migrate, and shows whether the swap passes your rules before it reaches customers.

Why now

Models change. Your product shouldn't.

The model behind your product is not permanent. Providers retire old versions, serving behavior can drift, and lower-cost alternatives appear constantly. Switching without evidence risks regressions. Refusing to switch means continuing to overpay.

Forced migrations

Providers retire models on fixed deadlines. Your team has to move before production requests begin failing.

Silent behavior changes

Infrastructure and serving changes can alter model behavior even when your application code has not changed.

Expensive inertia

A cheaper model may already handle your workload. Without a trustworthy test, the savings remain locked behind migration risk.

The platform

One test. A defensible decision.

01Real workload testing

Test what your customers actually use.

Import production traces from your existing observability stack, connect a lightweight recorder, or generate a starter suite from your prompts and documents. ACSI organizes the workload into representative test cases instead of relying on generic benchmarks.

  • Existing traces and exports
  • Lightweight recording
  • Starter suite generation
  • Stratified workload coverage
Evaluation datasetReady
Example data
Langfuse8,420 traces
LangSmithConnected
OpenTelemetryConnected
Prompt library34 templates
Documents126 files
2,480
selected cases
18
workload clusters
92%
observed traffic coverage
146
edge cases added

Illustrative: example workload sources.

02Variance calibration

Measure the model's natural wobble first.

The same model can return different answers to the same request. Before comparing replacements, ACSI tests the current model against itself and measures its normal run-to-run variation. Only degradation beyond that noise floor affects the verdict.

Without a control group, a model comparison can mistake normal variation for a real regression.

Baseline calibrationIllustrative

Current model vs. itself, across 5 runs per selected case.

Baseline variance±1.8%
Semantic agreement96.4%
Format variance0.3%
Calibration statusComplete
Baseline noise floor: ±1.8%. Only changes beyond this band affect the verdict.
Candidate delta−0.7%
Inside baseline variance
Candidate delta−4.9%
Material regression

Illustrative: normal variation vs. a real regression.

03Cost-aware migration

Find the cheapest model that passes.

ACSI starts with the lowest-cost viable candidate and stops at the first pass. Each candidate is tested with your existing prompts and then tested again with prompts adapted to the replacement model. The resulting prompt patches are included in the migration package.

  • Cheapest viable candidate first
  • Existing prompts tested unchanged
  • Model-specific prompt adaptation
  • Reviewable prompt diffs and holdout validation
Candidate searchBy projected cost
Illustrative
Candidate AExisting prompts + migrated prompts61% lower costBlock
Candidate BPasses on migrated prompts49% lower costPass
Candidate CSearch halted before reaching it31% lower costNot tested

Search stopped at first passing candidate.

Candidate B detail

Existing prompt resultBlock
Migrated prompt resultPass
Prompt patches6
Holdout resultPass

Illustrative: generic candidate names.

04Migration certificate

Ship the evidence, not a guess.

The result is a conservative PASS or BLOCK verdict against your own requirements, at stated coverage and confidence. The report shows what passed, what failed, what changed, how much the swap could save, and exactly what was not tested.

1Customer assertions
2Deterministic checks
3Independent model judges
4Human calibration sample
Benchmark: Opus 4.1 → Sonnet 5 migration, certified. Read the signed report
Migration verdictIllustrative
Lower-cost modelPass
Test cases2,480
Workload coverage92%
Confidence95%
Customer assertions passed14 / 14
Judge/human agreement91%
Prompt patches6
Projected model-cost reduction49%
ExcludedMulti-turn & autonomous-agent workflows

A PASS is evidence against the stated test scope and customer rules. It is not a guarantee of error-free production behavior.

Illustrative: example verdict values.

Continuous assurance

The migration ends. The test keeps watching.

The workload suite created for the migration stays installed as a permanent tripwire. ACSI reruns it on a schedule and alerts your team when the current model's behavior changes, or when a cheaper candidate clears your bar.

Migration is the event. Monitoring is the subscription.

Golden suite monitorLive
Illustrative timeline
  • Jul 2Baseline established
  • Jul 5No material change
  • Jul 8Format regression detected
  • Jul 8Alert sent to on-call
  • Jul 10Baseline restored
Healthy
Current status
3h ago
Last run
2,480
Cases monitored
±1.8%
Baseline variance

New candidate detected

Estimated cost reduction23%
StatusScreening
Open alerts0

Security

Your workloads stay under your control.

ACSI scrubs sensitive fields before evaluation and limits each run to the providers and environments you approve. Where supported, the full test can execute inside your existing cloud environment.

Sensitive-data scrubbing

Names, emails, credentials, API keys, and configured secrets are removed before testing.

Approved providers only

Raw workloads are never sent to a model provider the customer has not approved.

In-environment execution

Where supported, tests run through models available inside the customer's AWS, Azure, or Google Cloud environment.

Controlled retention

Evaluation inputs, outputs, reports, and retention policies are visible and configurable.

Replayed in your environment. Evidence comes out.

Methodology

Built to separate real regressions from noise.

Calibrated baseline

The current model is tested against itself before any replacement is judged.

Customer rules first

Schemas, required facts, executable code, format requirements, and other deterministic assertions outrank subjective scores.

Independent judging

Subjective cases use judges that are independent from the candidate models, with human calibration reported alongside them.

Explicit uncertainty

Every result states its test count, coverage, confidence, assumptions, and exclusions.

Read the methodology

Pay for the migration. Keep the alarm.

ACSI is priced per certified model swap, with optional continuous monitoring afterward. Model inference used during testing is passed through separately.

Find out whether you can switch before you risk it.

Test a lower-cost model against the workloads and rules that matter to your product.