Building the independent standard for AI workers.
Credenva evaluates AI workers as a whole — not isolated models, not demonstrations. Our mission is to give enterprises the same rigor for AI workers that they expect from financial audits and safety certifications.
Independent evidence for decisions that carry operational risk.
Enterprises are deploying AI systems that speak to customers, approve refunds, escalate incidents and shape reputational outcomes. Yet the evaluation practice around these systems has lagged behind the pace of AI adoption.
Credenva exists to close that gap with an independent, evidence-based methodology. We assess the operational AI worker — model, knowledge base, business rules, tools, permissions and human handoff — against standardized real-world job scenarios.
Our goal is a durable, vendor-neutral standard that answers a single executive question: Is this the right AI worker for this business role?
Model benchmarks, LLM comparison sites and developer eval tooling do not answer the enterprise question.
Model leaderboards are not AI workers
A capable base model is only one component. Enterprises deploy instructions, retrieval, policies, integrations and escalation — and it is that composite system that must be trusted.
Dev tools measure iteration, not readiness
Application evaluation platforms optimize development quality. They do not produce auditable evidence for governance, procurement or board-level risk decisions.
Buyers need independent evidence
Vendor-published metrics cannot substitute for third-party assessment. Trusted AI hiring requires an independent party applying the same methodology to every system.
How Credenva is being built.
Credenva is in an intentional, staged build. Public registry publication will not be issued until methodology, pilots and external review are complete.
- 2024Complete
Origin & thesis
Credenva was founded on the observation that enterprises had no independent way to answer whether a specific AI worker was ready for production — only model benchmarks, LLM comparison sites and vendor-authored demos.
- Early 2025Complete
Methodology draft v0.1
Initial evaluation pillars, scenario taxonomy and scoring framework drafted for AI AI customer-support workers — the first category Credenva evaluates.
- 2025In progress
Pilot program
Working with early vendors, enterprise buyers and support leaders to validate scenarios, calibrate scoring and stress-test the methodology on real AI workers.
- 2026Planned
External review & v1.0
Independent methodology review, publication of the versioned framework, and issuance of the first non-illustrative Credenva assessments.
- 2026 →Roadmap
Expansion beyond support
Extend the framework to adjacent role categories — sales operations, internal knowledge workers, back-office automation — under the same evidence discipline.
A world where every enterprise AI worker carries independent, comparable evidence.
We envision a future in which procurement teams, risk officers and boards can compare AI workers the same way they compare audited financial statements or safety-certified equipment — using standardized, third-party evidence.
Credenva assessments should be legible to a customer-support director, an internal auditor and a regulator alike. That means versioned methodology, transparent limitations and evidence that can be replayed and re-examined.
A methodology designed to be scrutinized, not marketed.
Vendor-neutral
Credenva does not sell AI systems, prompts, integrations or infrastructure. No commercial relationship with a vendor influences a score.
Standardized scenarios
Every AI worker is assessed against the same versioned scenario library — routine, complex, adversarial and high-risk workflows.
Auditable evidence
Prompts, tool calls, responses, timing and outcomes are captured and preserved. Assessments can be replayed and independently reviewed.
Transparent versioning
Methodology versions, limitations, sampling approach and change history are published alongside every result.
Full methodology, scoring pillars and critical-failure definitions are published in the assessment framework and documentation.
From pilot methodology to a recognized standard.
Credenva is designed to graduate from an independent evaluation initiative into a durable industry standard. Progression is evidence-gated — each stage requires external validation before the next begins.
Pilot methodology
Draft framework validated against a small cohort of real AI workers under NDA.
External review
Independent reviewers assess scenario coverage, scoring calibration and evidence handling.
Public v1.0 standard
Versioned public methodology, published assessments and open change history.
Cross-category standard
Framework extended beyond customer support with the same evidence and independence discipline.
Credenva is currently operating a methodology-development and pilot program. Draft scores and reports are illustrative and must not be represented as accredited, regulatory or standards-body accreditation.