Count vs Langdock: Governed AI vs Trusted Answers [2026]
Langdock gives European companies governed access to AI. Count makes sure the research and analysis that AI produces can be checked before anyone acts on it.
Langdock is a Berlin-based AI workspace for European companies: chat, agents and workflows across many models, hosted in Germany, with governance templates for the EU AI Act. Count is a collaborative platform for AI-powered research and analysis that shows the reasoning chain behind every answer, and it can host and process your data in the EU too.
Langdock governs how your company uses AI. Count shows whether what the AI concluded is right.
Is a governed AI a trustworthy one?
Not on its own. Governance answers the questions a security and legal team asks: where the data lives, which models are approved, who can build an agent, what gets logged. Those questions matter, and Langdock answers them carefully (trust centre).
But a fully governed AI can still produce a confident claim with nothing under it. The reader of the answer has a different question: what does this claim rest on? That is the question Count answers, for every claim, with a reasoning chain from the claim back to its source.
Citations in a report vs a check on every claim
Langdock's research reports include citations, which show where the agent looked. They do not show whether each source supports the sentence it is attached to, or whether the conclusion follows from the evidence. Count labels each claim as cited, assumed, model knowledge or a potential hallucination, and the chain makes logic gaps visible as well as missing sources.
Shared chats vs a shared canvas
In Langdock, colleagues share chats and projects. In Count, people and the agent work on the same canvas in real time, comment on individual claims, and turn the result into a report or deck with the reasoning still attached.
Usage limits
Langdock applies fair-use limits per five-hour session and per week, plus a message cap; at the limit, users buy extra usage or drop to a fallback model. Count Pro includes unlimited AI credits on a fair-use basis, and Count picks the right model for each step.
Why research teams choose Count over Langdock
- Every claim checked, with unsupported claims flagged automatically.
- Analysis that lasts. Langdock's Data Analysis runs Python in short sessions whose files are cleared when idle; Count keeps research, queries and charts on a canvas the team returns to.
- Live reports, scheduled reports and alerts built from the research.
- EU hosting as well. Count offers EU and US data residency, is SOC 2 compliant and follows GDPR.
- Works with your other assistants. Count's MCP server checks answers from Claude, ChatGPT and other tools in one place.
“Count is incredibly helpful at just about every step of my data work, whether it's shared brainstorm sessions, quick checks or debugging 13 levels deep when no one has a clue what's going on and no other tool would provide such transparent overview.” - Veronika Cucorova, Senior Data Engineer at Otrium (review on G2)
Langdock and Count compared
| Capability | Langdock | Count |
|---|---|---|
| Hallucination detection | No - citations in research reports, but unsupported claims are not flagged | Yes - every claim traced to its source, assumption or inference, and unsupported claims flagged |
| No usage caps | No - fair-use limits per session and per week | Yes - unlimited AI credits on Pro, on a fair-use basis |
| Live reports | No - analysis results stay in the chat | Yes - live reports, scheduled reports and alerts |
| Semantic layer | No | Yes - Count Metrics, with governance and change approvals on Enterprise |
| Agent skills | Yes - agents, skills and shared prompts | Yes - agent skills and context shared across the workspace |
| Real-time collaboration | No - shared chats and projects | Yes - multiplayer canvas, with free viewers |
| MCP connections | Yes - MCP client and an agent MCP server | Yes - connects to MCP servers, and has its own MCP server |
| Native database connections | No - BigQuery and Snowflake only through agent integrations | Yes - Snowflake, BigQuery, Databricks, Postgres, Redshift and more |
| Python support | Yes - Data Analysis runs Python | Yes - Python and SQL on the same canvas |
For AI workspaces as a group, see Count vs AI workspaces. For Dust, see Count vs Dust.
FAQs
Yes. Count offers EU and US data residency, is SOC 2 compliant and follows GDPR.
Langdock's research reports include citations, but it does not flag claims that their sources fail to support. Count flags unsupported claims automatically.
For research and analysis, yes. Count adds claim-level checking, a real-time canvas and live reports on top of agents, skills and MCP connections.
Count has a Free plan. Pro is $49 per editor per month with free viewers and unlimited AI credits on a fair-use basis. Enterprise adds SSO, SCIM and EU/US data residency.