Registry › Compare › Docling vs WrenAI

Docling vs WrenAI

Both are Grade A and 4.6 points apart, so choose on what you weigh most. Docling leads on maintenance and adoption, and rests on broader evidence.

A Docling 89.6

Get your documents ready for gen AI

docling-project/docling · #31 overall · #1 Research & Data · coverage A (4/5)

Choose Docling if maintenance and adoption matter most.

+6.7Adoption: 867.2k weekly downloads against 87
+2.1Maintenance: last push today, against 2d ago
A vs BEvidence coverage: 4 of 5 independent signal types, against 3

A WrenAI 85.0

GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.

Canner/WrenAI · #92 overall · #4 Research & Data · coverage B (3/5)

WrenAI doesn't lead on any scored dimension in this pair.

Where they differ

18.7

Safety / IntegrityWrenAI +0.3

19.0

12.9

TransparencyWrenAI +0.3

13.2

20.0

MaintenanceDocling +2.1

17.9

19.5

AdoptionDocling +6.7

12.8

+0.5

Runtime calibrationWrenAI +3.6

+4.1

1 dimension identical: Identity 18.0 · Full evidence table

An independent, evidence-based trust comparison of Docling and WrenAI, two Research & Data projects in the HVTracker registry. Scores come from public, checkable signals — supply-chain provenance, OSSF Scorecard, maintenance, and adoption — not popularity.

Full evidence

Signal	Doclingdocling-project/docling	WrenAICanner/WrenAI
HVTrust score	89.6	85.0
Evidence grade	A	A
Coverage grade	A	B
Overall rank	#31	#92
Rank in Research & Data	#1	#4
GitHub stars	69.1k	17.9k
Last updated	today	2d ago
Build provenance	Yes	Yes
OSSF Scorecard	5.2 / 10	5.5 / 10
License	MIT	NOASSERTION
Downloads	867k/wk	87/wk
Trust dimensions (points earned)
Safety / integrity / 25	18.7	19.0
Identity & provenance / 18	18.0	18.0
Transparency / 17	12.9	13.2
Maintenance / 20	20.0	17.9
Adoption / 20	19.5	12.8
Runtime capability surface (full matrix)
MCP server	Implemented	Implemented
External providers	1 — OpenAI	3 — Amazon Bedrock, Anthropic, Postgres
Requires API keys	No	No
Plugin surface	plugins	plugins
Provenance drift	Unknown	Match

Open in the live compare tool → Docling profile WrenAI profile More Research & Data →

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 →