Test, evaluate, and certify AI models for trust
Seekr’s independent AI testbed certifies AI models for security, reliability, and bias-resistance, ensuring AI workflows and decisions are secure and transparent.
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Problem
The rapid spread of unvetted AI models exposes U.S. systems and decision-making to adversarial manipulation, embedded bias, and strategic vulnerabilities at scale.
Inadequate benchmarks
Generic benchmarks miss mission-critical needs, making AI ineffective and unreliable.
Adversarial threats
Adversaries manipulate models through hidden prompt injections and data poisoning.
Ideological bias
Hostile models embed political and cultural biases to distort truth and sow division.
Disinformation surge
Deepfakes and deceptive content erode trust and credibility.
Operational blind spots
Context-free, untested models mislead users and jeopardize integrity and security.
How it works
Choose your model
Select from hosted LLMs or upload your own for evaluation
Configure your test run
Combine industry benchmarks, custom datasets, and evaluators to simulate real-world use.
Customize your stack
Add your own QA pairs, bias probes, and evaluators—human or AI—to tailor assessments to your use case.
Run the evaluation
Models are evaluated for bias, accuracy, and relevance across chosen scenarios.
Review actionable results
Get a clear Test Summary and Model Test Card with insights and transparency.
Export trusted models
Validated models are ready for secure deployment in mission-critical environments.
Value
Seekr is committed to the safe adoption of trusted, reliable, and valuable models. That’s why Seekr offers model evaluation capabilities that certify models for trust, security, and reliability—offering transparent risk scoring, flexible testing, custom evaluators, continuous safeguards, and audit-ready governance.
Clear scoring
Transparent benchmarking delivers side-by-side model scorecards across real-world scenarios for every model.
Flexible testing
Mix and match datasets, evaluators, and models (open weights or proprietary) to run targeted, domain-specific tests.
Customizable evaluators
Build custom tests to probe edge use cases based on intended model use.
Always-on safeguards
Continuous guardrails catch drift, hallucinations, and safety issues.
Audit-ready governance
Built-in logs track every test, dataset, and result, for full accountability.
Built on SeekrFlow
Edge-Compatible Data Engine
Parses scan logs, label files, and routing data from decentralized systems
Agent Framework
Planner and Evaluator agents coordinate multi-step investigations.
LLM-RAG
Generates grounded, natural language explanations for suspicious label behavior
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See it in action
See how this AI solution works for your team. Request a live walkthrough with one of our experts and explore how it can adapt to your unique workflows and data.
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