AANCER vs Langdock:
enterprise AI that stays inside your perimeter.

1 · Enforcement in code decides the boundary, not the hosting region

Langdock's trust story is real. Its default is EU-hosted cloud on Azure, it aligns to GDPR, and it holds ISO 27001 and SOC 2 Type II today, certifications AANCER is still working toward because our ISO is in progress. If the requirement is European hosting with a certified vendor and no infrastructure to run, Langdock meets it well.

AANCER answers a stricter question: the platform must enforce the data boundary itself, not describe it in a policy. AANCER runs on your servers, your Kubernetes, or a fully air-gapped network. A fail-closed policy engine sits inside the runtime, so a request that would send protected data to a cloud model returns 403 SOVEREIGNTY_BLOCK before it leaves your network, and the refusal is written to the audit ledger. EU hosting keeps data in a region; the AANCER runtime keeps it inside a boundary you define.

With Langdock the guarantee is a region and a certificate; with AANCER a request that would breach the boundary is refused in code and logged before it leaves your network.

2 · Sovereign deployment without a seat floor

Langdock does offer sovereign deployment, and the options are real: single-tenant SaaS, bring-your-own-cloud, and on-prem via Helm and Kubernetes. The constraint is scale. Single-tenant is an enterprise tier that starts at 2,000 seats, while BYOC and on-prem start at 5,000 seats. For an organization of that size, those options are genuine.

AANCER attaches no seat floor to the same outcome. On-prem, private-cloud, and air-gapped deployment are available from the free EVAL edition, at any size, with every user included. A 40-person compliance team can run the identical air-gapped platform that a 40,000-person institution runs. The deployment is licensed once, and adoption does not raise the bill.

3 · Local models by default, not cloud APIs reached by key

Langdock is model-agnostic in a useful way: 30 to 35 or more models across six providers, selected with your own keys. That breadth is a genuine strength for teams that want to route between frontier models.

The difference is where those models run. Langdock's open-weight options, such as Llama, Mistral, and DeepSeek, are offered as cloud APIs, and running them on your own hardware is not something Langdock documents either way. AANCER runs local models on your hardware by default and treats cloud providers as an option that policy has to permit, per step. In a sovereign workspace the model stays inside the perimeter alongside the data.

4 · Assistants that answer, and agents you can certify and revoke

Langdock's agents are bounded assistants: specialized chatbots with personas and form triggers, paired with a mature no-code workflow builder that offers versioning, run history, and human-in-the-loop steps. For many teams that is a sensible and safe shape for automation, and Langdock executes it well.

AANCER's agents carry signed passports. An agent can only touch a tool, a budget, or a workspace it was granted, revoking it stops it within 30 seconds, and every action it takes lands in an append-only, hash-chained audit ledger rather than a run history. When an auditor asks what an agent did and under whose authority, the answer is a tamper-evident record instead of a log you are asked to trust.

Where Langdock is ahead is worth stating plainly. It holds ISO 27001 and SOC 2 Type II today, its managed EU cloud removes the operational load, and its workflow builder is mature. AANCER trails on held certifications: our controls are mapped to 27 regulations and our audit chain is verifiable, but our ISO is still in progress. If a filed certificate is what procurement needs above every other factor, Langdock is ahead today. If enforcement in code, deployment freedom, and provable agent governance decide it, AANCER is built for that.