Registry › Compare › LangWatch vs Weights & Biases Weave

LangWatch vs Weights & Biases Weave

Both are Grade A and 2.0 points apart, so choose on what you weigh most. LangWatch leads on maintenance; Weights & Biases Weave leads on supply-chain integrity and transparency.

A LangWatch 86.7

Open-Source Agent Observability & Evals for AI Platform teams. Trace, test, route and govern every agent & coding assistant in the company.

langwatch/langwatch · #76 overall · #3 Observability & Evaluation · coverage A (4/5)

Choose LangWatch if maintenance matters most.

+0.9Maintenance: last push today, against 1d ago

A Weights & Biases Weave 84.7

Weave is a toolkit for developing AI-powered applications, built by Weights & Biases.

wandb/weave · #98 overall · #5 Observability & Evaluation · coverage A (4/5)

Choose Weights & Biases Weave if supply-chain integrity and transparency matter most.

+2.2Safety / Integrity: 87% of recent commits signed, against 82%
+1.2Transparency: OSSF Scorecard 6.4 against 4.9

Where they differ

17.7

Safety / IntegrityWeights & Biases Weave +2.2

19.9

12.7

TransparencyWeights & Biases Weave +1.2

13.9

20.0

MaintenanceLangWatch +0.9

19.1

15.4

AdoptionLangWatch +0.4

15.0

+2.9

Runtime calibrationLangWatch +4.1

-1.2

1 dimension identical: Identity 18.0 · Full evidence table

An independent, evidence-based trust comparison of LangWatch and Weights & Biases Weave, two Observability & Evaluation projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.

Full evidence

Signal	LangWatchlangwatch/langwatch	Weights & Biases Weavewandb/weave
HVTrust score	86.7	84.7
Evidence grade	A	A
Coverage grade	A	A
Overall rank	#76	#98
Rank in Observability & Evaluation	#3	#5
GitHub stars	5.0k	1.1k
Last updated	today	1d ago
Build provenance	Yes	Yes
OSSF Scorecard	4.9 / 10	6.4 / 10
License	Apache-2.0	Apache-2.0
Downloads	83k/wk	528k/wk
Trust dimensions (points earned)
Safety / integrity / 25	17.7	19.9
Identity & provenance / 18	18.0	18.0
Transparency / 17	12.7	13.9
Maintenance / 20	20.0	19.1
Adoption / 20	15.4	15.0
Runtime capability surface (full matrix)
MCP server	Implemented	Implemented
External providers	1 — Anthropic	8 — Amazon Bedrock, Anthropic, Cohere, …
Requires API keys	No	Yes
Plugin surface	plugins	—
Provenance drift	Partial	Partial

Open in the live compare tool → LangWatch profile Weights & Biases Weave profile More Observability & Evaluation →

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption, scaled by an evidence-confidence factor. Grade bands: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Signals refresh daily. Full methodology v4.4 →