Private Model Evaluation
Private Recognition Model Evaluation
Evaluate InsightFace private recognition models using your own validation data before making a commercial licensing decision.
For enterprise teams, model performance should be validated against real-world business scenarios. InsightFace offers a structured private model evaluation process to help qualified teams compare open-source models, private models, and deployment options.
How the evaluation works
A six-step process designed for enterprise procurement
Submit evaluation request
Send us a brief description of your team, use case, and target deployment via the enterprise inquiry form.
Share your use case and deployment requirements
Walk our team through your validation goals, data characteristics, expected volume, and deployment preferences (Cloud API, on-premise, or edge).
Complete evaluation agreement if required
Where appropriate, both sides put a lightweight evaluation agreement in place to cover scope, confidentiality, and acceptable use.
Receive private API access or evaluation instructions
Qualified teams receive credentials for a private model endpoint or, for on-premise scenarios, instructions to evaluate inside their own environment.
Benchmark with your own validation data
Run identity verification, KYC, 1:N search, or access-control workloads on your own datasets and compare directly with your current vendor or open-source baseline.
Choose a commercial licensing or deployment plan
Based on the results, choose the licensing, API, SDK, or custom cooperation plan that fits your business needs.
Who this is for
The private model evaluation process is designed for qualified enterprise and research teams. Access, duration, and modality (API or on-premise) are confirmed during scoping and may vary subject to review.
Enterprise teams making a near-term commercial licensing decision.
Teams with validation data representative of their production scenarios.
Teams able to commit engineering time to running and interpreting the benchmark.
Engineering support
Hands-on help during evaluation
Our team can help with SDK integration, threshold tuning, and result interpretation throughout the evaluation so you can finalize a decision with confidence.
Integration guidance for the Cloud API, the InspireFace SDK, or on-premise model deployment.
Threshold tuning advice for verification, identification, and 1:N search workloads.
Help interpreting accuracy, false match rate, and latency under your operating conditions.
Ready to start a private model evaluation?
Submit an enterprise inquiry with a short description of your use case, deployment, and expected volume. We will follow up to scope the evaluation.