M365 Copilot Evals vs LangSmith vs Braintrust vs Arize (May 2026)

Four agent evaluation platforms going head-to-head. Here’s exactly which one fits which stack as of May 2026 — including the new Microsoft 365 Copilot Agent Evaluations CLI in public preview this month.

Last verified: May 18, 2026

TL;DR table

	M365 Copilot Agent Evaluations	LangSmith	Braintrust	Arize Phoenix
Vendor	Microsoft	LangChain	Braintrust	Arize AI
Stage	Public preview (May 2026)	GA	GA	GA
Framework scope	M365 Copilot only	LangGraph / LangChain native, others via SDK	Any	Any (OpenTelemetry-native)
LLM judge	Azure OpenAI only	Any	Any	Any
Single + multi-turn	✅	✅	✅	✅
Built-in metrics	7 (Relevance, Coherence, Groundedness, Similarity, Citations, ExactMatch, PartialMatch)	Many (custom + library)	Many (custom + library)	Many (custom + library)
CI/CD reports	✅ HTML/JSON/CSV	✅	✅	✅
Dataset versioning	Limited	✅	✅	✅
Production observability	Through Agent 365	✅	✅	✅ (OTel-first)
Open source	No	No (cloud)	No	✅ Phoenix (Apache 2.0)
Pricing	Free with M365 Copilot + Azure OpenAI judge	Free tier → $39/seat/mo +	Free tier → $99/mo + usage	Free (self-host) + cloud paid
Best for	M365 Copilot agents	LangGraph / LangChain teams	Production LLM ops at scale	OTel-native, OSS-leaning

When each one wins

Use M365 Copilot Agent Evaluations when:

• You ship declarative agents into Microsoft 365 Copilot.
• You’re already paying for M365 Copilot licenses and Azure OpenAI.
• You want a Microsoft-supported, first-party path that won’t go EOL when you upgrade Copilot.
• You don’t need framework portability.

Use LangSmith when:

• Your agents are LangGraph or LangChain native.
• You want tight integration with LangSmith Hub for prompt management.
• You need playground + tracing + eval in one product.
• You’re paying LangChain anyway for LangGraph Cloud.

Use Braintrust when:

• You want the most polished SaaS UX for evals + production logging.
• Framework-agnostic (you might use LangGraph today, Mastra tomorrow, custom Python next year).
• You need strong dataset/experiment versioning.
• Your team has the budget for a premium tool.

Use Arize Phoenix when:

• You want OpenTelemetry-native observability for LLM apps.
• You prefer open source with optional cloud upgrade.
• You want one tool for evals + production tracing across many frameworks.
• You’re already on Arize for ML observability.

The agent eval loop (universal)

Prompts (dataset)
   │
   ▼
Agent under test ──► Response
   │                   │
   │                   ▼
   │            LLM judge / rule-based metric
   │                   │
   ▼                   ▼
Versioned dataset ──► Scored experiment ──► CI/CD gate

All four tools implement this loop. The differences live in:

1. Where you authenticate (M365 tenant vs cloud account).
2. Which judge you can plug in.
3. How datasets are versioned.
4. What production observability looks like after deployment.

Feature deep dive

Coverage of eval types

Eval type	M365	LangSmith	Braintrust	Arize
Reference-free (Relevance, Coherence)	✅	✅	✅	✅
Reference-based (Similarity, ExactMatch)	✅	✅	✅	✅
RAG metrics (Groundedness, Citations)	✅	✅	✅	✅
Tool-call correctness	Limited	✅	✅	✅
Multi-agent trace evaluation	Limited	✅	✅	✅
Custom code metric	Limited	✅	✅	✅

If your agents do heavy tool calling or multi-agent orchestration, LangSmith / Braintrust / Arize go deeper than the M365 preview today.

Production logging

	Real-time prod logging	Sampling	Drift detection
M365 Copilot Evals	Via Microsoft Agent 365	Limited	Limited
LangSmith	✅	✅	✅
Braintrust	✅	✅	✅
Arize Phoenix	✅ (OTel)	✅	✅

For mission-critical agents in production, you need real-time logging. M365 partially delegates this to Microsoft Agent 365’s monitoring; the other three handle it natively.

Pricing reality

	Starter	Production
M365 Copilot Evals	Free with M365 Copilot license	+ Azure OpenAI judge usage (~$50-500/mo for moderate eval volume)
LangSmith	Free tier (1 dev)	$39/seat/mo + usage; enterprise custom
Braintrust	Free tier	$99/mo Pro + usage; enterprise custom
Arize Phoenix	Free (self-host OSS)	Arize cloud paid (custom enterprise)

Hidden cost across all four: the LLM judge model. Running GPT-5.5 as a judge on 10,000 multi-turn evals is not cheap. Use GPT-5.5-mini or Claude Haiku 4.5 as judge where quality allows.

Decision flowchart

Where do your agents live?
├─ Microsoft 365 Copilot tenant
│   └─► M365 Copilot Agent Evaluations (primary)
│        + Braintrust or Arize for cross-tenant ops
│
├─ LangGraph / LangChain stack
│   └─► LangSmith
│
├─ Framework-agnostic, premium SaaS budget
│   └─► Braintrust
│
└─ OpenTelemetry / OSS-first
    └─► Arize Phoenix (+ Arize cloud if you scale)

Combination strategy

Sophisticated teams in May 2026 run two evaluation tools:

1. CI/CD eval — fast, deterministic regression checks on every PR. (LangSmith or Braintrust or M365 Evals)
2. Production observability — real-time tracing + drift detection on live traffic. (Arize Phoenix or LangSmith or Braintrust)

Microsoft customers add M365 Copilot Agent Evaluations for Copilot-specific gates, then layer Braintrust or Arize across the wider ecosystem.

What’s next

• M365 Copilot Evals — cross-OS support, custom evaluator plug-ins, dataset versioning.
• LangSmith — deeper LangGraph Cloud integration.
• Braintrust — more multi-agent trace tooling.
• Arize Phoenix — continued OpenTelemetry-first work + Phoenix OSS growth.

TL;DR

Pick M365 Copilot Agent Evaluations for M365 Copilot agents. Pick LangSmith if you live on LangGraph. Pick Braintrust for the most polished cross-framework SaaS. Pick Arize Phoenix if you want OpenTelemetry + open source. Most production teams will end up running two — one for CI/CD, one for live observability.

---

Related reading

• What is M365 Copilot Agent Evaluations Tool? (May 2026)
• What is Claude Managed Agents Outcomes? (May 2026)
• Claude managed agents Outcomes vs LangGraph vs CrewAI (May 2026)
• Best AI agent control planes (May 2026)

Sources: Microsoft 365 Dev Blog public preview announcement, microsoft/m365-copilot-eval GitHub, LangSmith docs (smith.langchain.com), Braintrust docs (braintrust.dev), Arize Phoenix docs (docs.arize.com/phoenix) — May 2026.