Top AI Evaluation Tools for Enterprises in 2026

Enterprise AI deployment is moving faster than evaluation practices can keep up. Organizations are shipping LLM-powered features across healthcare, finance, legal, and education, yet most evaluation tooling was built for research benchmarks rather than regulated production environments. The distance between "the model works" and "we can demonstrate that to our compliance team" is exactly where enterprise AI projects tend to stall.

The costs of this gap are already visible in public. In mid-2025, Deloitte submitted an AU$440,000 government report containing fabricated citations and non-existent court references, all generated by GPT-4o. The errors were caught by a university researcher, not Deloitte's internal review process. Deloitte issued a partial refund. The incident reflects a pattern now routine across enterprises: AI outputs flow into high-stakes workflows without domain expert review, and generic quality checks fail to catch domain-specific failures.

We assessed seven enterprise AI evaluation platforms for 2026. The tools differ in deployment flexibility, compliance posture, and whether they actually address what enterprises need evaluated. SSO and encryption are table stakes at this point, but the harder question is whether a platform can encode your organization's quality standards into automated evaluations that domain experts, not just engineers, can define and trust.

Comparison at a glance

What enterprise AI evaluation actually requires

Standard LLM evaluation measures accuracy, relevance, and toxicity. Enterprise evaluation layers in organizational requirements that most open-source frameworks were never built to handle:

• Compliance evidence: audit-ready records with reproducible results and clear trails for regulators and internal governance, not just binary pass/fail scores
• Domain expert involvement: the people who define quality (physicians, attorneys, compliance officers) rarely write evaluation code, and most platforms do nothing to bridge that gap
• Deployment control: data residency requirements, self-hosting mandates, and air-gapped environments rule out SaaS-only platforms for many regulated organizations
• Stakeholder alignment: legal, compliance, product, and engineering teams need shared quality definitions, not siloed metrics that only engineers can interpret

Most platforms handle deployment control reasonably well. Compliance evidence is improving across the board. Domain expert involvement is where the gap persists.

Platform breakdowns

1. Truesight

Enterprise AI teams face a persistent mismatch: the people who know what "good" looks like (clinicians, compliance officers, educators, financial analysts) rarely write evaluation code. Truesight is built to address that directly. Domain experts set quality criteria through a guided, no-code interface, and those criteria get deployed as automated evaluations running against production AI outputs. The platform is purpose-built for organizations where output quality is a regulatory or reputational concern, not a nice-to-have.

• Guided, no-code setup for non-technical domain experts
• Live API endpoints deploy evaluations directly to production pipelines
• Systematic error analysis to surface evaluation criteria from real data
• Multi-model support: OpenAI, Anthropic, Google, any LiteLLM provider
• SME review queue with frozen config snapshots for audit provenance

Best for: Regulated industries (healthcare, finance, legal, education) where domain experts must define and validate quality standards.

2. Arize Phoenix

Built entirely on OpenTelemetry with no proprietary tracing layer, so instrumentation stays portable and vendor-agnostic. Backed by strong funding (including a $70M Series C in 2025), with enterprise customers including Uber, Booking.com, PepsiCo, and Duolingo.

• Free self-hosting via Docker, Kubernetes, or AWS CloudFormation with no feature restrictions
• SOC 2 Type II, HIPAA, GDPR compliance with US/EU/CA data residency options
• LDAP authentication with group-based role mapping and TLS encryption
• OpenTelemetry-native: vendor-agnostic, portable instrumentation
• Alyx AI copilot for trace troubleshooting and prompt optimization (AX tier)

Best for: Organizations requiring fully self-hosted, air-gapped deployment with zero vendor lock-in.

3. LangSmith

A strong enterprise fit for organizations running LangChain or LangGraph. Deployment options span cloud SaaS, hybrid BYOC (data plane in the customer VPC), and fully self-hosted via Kubernetes. Available on AWS Marketplace for streamlined enterprise procurement. The product works best within LangChain and LangGraph pipelines.

• Three deployment modes: cloud, hybrid BYOC, and fully self-hosted
• HIPAA, SOC 2 Type 2, GDPR compliance with SSO/SAML and SCIM provisioning
• AWS Marketplace availability for enterprise procurement workflows
• 400-day extended trace retention for audit and compliance evidence
• Polly AI assistant for in-app trace analysis and debugging

Best for: Large organizations already running the LangChain ecosystem that need F500-grade deployment flexibility across cloud and self-hosted options.

4. Braintrust

A practical option for teams with data sovereignty requirements. Braintrust's hybrid self-hosting model runs the data plane in the customer's AWS, GCP, or Azure environment while the control plane (UI and metadata) stays in Braintrust's cloud. The browser connects directly to the customer's data plane via CORS, so customer data never flows through Braintrust infrastructure. Per-organization pricing with unlimited users on all tiers.

• Hybrid self-hosting: customer data stays in the customer VPC
• SOC 2 Type II and HIPAA compliance with AES-256 API key encryption
• Per-organization pricing with unlimited users and no per-seat cost scaling
• AWS Marketplace listing for enterprise procurement
• Notable customers: Stripe, Notion, Instacart, Zapier, Dropbox

Best for: Teams that need data sovereignty without the operational overhead of managing full self-hosting.

5. Weights & Biases Weave

The broadest compliance certification set on this list: SOC 2 Type II, ISO 27001, ISO 27017, ISO 27018, HIPAA, NIST 800-53, and GDPR alignment. Now part of CoreWeave following the 2025 acquisition, which provides strong infrastructure backing but introduces some product roadmap uncertainty. Dedicated single-tenant cloud is available across AWS, GCP, and Azure. One limitation worth noting for some teams: Weave-specific BYOB constraints apply on certain managed plans.

• SOC 2, ISO 27001/27017/27018, HIPAA, NIST 800-53, GDPR compliance
• Dedicated single-tenant cloud with IP allowlisting and private connectivity
• Self-managed deployment via Kubernetes with Helm charts (licensed)
• SSO via Google, GitHub, Okta, Azure AD with SCIM provisioning and PII redaction
• Widely adopted across enterprise and research AI teams

Best for: Organizations where compliance certification coverage is the primary criterion for vendor selection.

6. Comet Opik

Apache 2.0 licensed with no restrictions, making it one of the most permissive open-source options for enterprise deployment. Self-hostable via Docker (single-command setup) or production Kubernetes with Helm charts. The architecture uses ClickHouse for analytics, designed to handle high-volume trace workloads. All paid plans include unlimited team members, and the $19/month Pro tier is the lowest starting price on this list.

• SOC 2, ISO 27001, ISO 9001, HIPAA, and GDPR compliance
• Apache 2.0 license with no managed-service restrictions
• Production Kubernetes deployment with ClickHouse analytics backend
• 2-hour enterprise support response SLA
• Unlimited team members across all plans

Best for: Organizations that want permissive open-source licensing paired with enterprise compliance certifications at the lowest price point.

7. DeepEval by Confident AI

One of the highest metric counts on this list, with 50+ built-in evaluation metrics, plus SOC 2 and HIPAA support on higher tiers. The enterprise tier includes dedicated on-premises deployment on AWS, Azure, or GCP with custom data residency options. The trade-off: Confident AI is a newer company with a shorter public enterprise track record compared to the more established platforms above. Python-only.

• SOC 2, HIPAA, and GDPR support on higher tiers
• Dedicated on-prem deployment on AWS, Azure, or GCP (enterprise tier)
• Custom data residency: US, EU, Canada, Australia, Japan
• 50+ evaluation metrics including 6 agent-specific and 5 RAG-specific
• Native Pytest integration for CI/CD evaluation pipelines

Best for: Python-first teams that need broad off-the-shelf metric coverage with flexible data residency options.

How to choose

Picking the right platform comes down to your deployment constraints, who needs to define quality in your organization, and where you fall on the build-vs-buy spectrum.

• Choose Truesight when regulated industries require domain experts to set and validate quality standards, and evaluations need to produce compliance evidence for auditors and internal stakeholders.
• Choose Arize Phoenix when fully self-hosted, air-gapped deployment with no feature gates is a hard requirement and OpenTelemetry portability matters to your team.
• Choose LangSmith when your organization needs F500-grade deployment options across cloud, hybrid, and self-hosted within the LangChain ecosystem.
• Choose Braintrust when data sovereignty is a requirement but you want to avoid the operational overhead that comes with full self-hosting.
• Choose W&B Weave when compliance certification coverage (SOC 2, ISO, NIST, HIPAA) is the primary criterion for your vendor selection process.
• Choose Comet Opik when permissive open-source licensing and production-scale self-hosting at the lowest price point are your top priorities.
• Choose DeepEval when you need the widest selection of off-the-shelf evaluation metrics with flexible data residency options for a Python-first team.

Disclosure: Truesight is built by Goodeye Labs, the publisher of this article. We have aimed to provide a fair and accurate comparison based on each platform's documented capabilities as of February 2026.