Human intelligence evaluates your LLMs, agents and voice assistants the way real users meet them, across languages, regions and domains.
The agent understands what the applicant is asking for.
The right tool is called with the right inputs.
The answer stays inside the rules the business set.
Automated scoring cannot settle it, so it goes to a person.
Matched by language, region and domain expertise.
The human judgement is recorded with the evidence.
Figures from published Oprimes programs.
Evaluation that stops at one response, one language or one team's own tests misses where real users get hurt.
A step that is right 95% of the time gives about 60% reliability across 10 steps. Evaluating one response at a time reports the first number. Customers live with the second.
A European bank's loan assistant passed every internal benchmark. Testing with real applicants found that second-language applicants were routed to manual review at a disproportionate rate, a pattern no benchmark by applicant language had tested.
A chatbot advising farmers had to be correct in Assamese and Tamil, not only Hindi and English. Native-speaker scoring, followed by an independent blind audit, confirmed the quality score instead of assuming it.
Gartner forecasts that over 40% of agentic AI projects will be cancelled by the end of 2027, citing escalating costs, unclear business value or inadequate risk controls. Source: Gartner forecast, June 2025
Choose the offering that matches what you are building.
Human-intelligence-powered evaluation of LLMs and AI features: human feedback, response scoring and validation by verified people.
Evidence of how your model behaves with the people it serves, before they meet it.
Testing of AI agents on whether they finish real tasks correctly and safely, across the whole workflow and not only the first step.
Agents that complete the whole task, not only the first step.
Evaluation of voice agents with real speakers across accents, dialects and environments.
Voice agents that understand people the way they actually speak.
Are answers and task results correct and grounded?
Does the output stay fair and factual across user groups and languages?
Does the system avoid harmful or non-compliant output?
Red teaming and adversarial testing by verified experts.
How well multilingual voice and chat agents hold up in real conversation.
The platform loop, applied to AI evaluation.
Reviewers matched by language, region and domain.
Rubrics, tasks and pass criteria, agreed up front.
Automated scoring covers volume. Human reviewers judge nuance, tone and edge cases.
Scores, findings and failure examples in dashboards.
Re-run after each model or prompt change.
Use cases from the platform, by technology and industry.
Figures from Oprimes-validated deployments.
Oprimes designs, runs and reports the program end to end.
Your own testers or panel, run on Oprimes workflows and quality controls.
Your team runs studies and evaluations on the platform.
The platform and crowd delivered under your brand.
SaaS and Managed are the common choices for continuous evaluation.
Automated judges score volume quickly. Human reviewers judge tone, ambiguity, cultural fit and domain correctness, and settle the cases where automated scoring is unsure. Oprimes combines both.
LLMs, AI agents, voice and chat assistants, vision and multimodal models, and AI-powered features inside applications.
Yes. We evaluate whether the agent completed the whole task, used the right tools and handed off to a person when it should.
Verified people matched by language, region and domain, including professionals from finance, legal, healthcare and technology.
Yes. Verified experts run adversarial and prompt-injection tests, and findings are tagged and routed to your engineering team.
Yes. Pre-release and proprietary models are supported, with NDAs, private task environments and secure access.
It produces documented, human-validated evidence that can be organised against frameworks such as the EU AI Act and the NIST AI Risk Management Framework. It does not replace legal advice.
Share a model, an agent or a workflow. We will scope an evaluation.
Evaluation you can show to your engineers, your customers and your auditors.
Book a 30-minute consultation with an Oprimes AI Trust Specialist. We will map your use case, recommend the right service pillar, and give you a delivery timeline before you commit to anything.
Trusted by 80+ enterprise AI teams across 6 industries. No obligation on first consultation.