Enterprise Adoption & Engineering

From ATF to your accepted AI platform.

Abillify helps companies build, integrate and operate audit-proof AI platforms based on ATF.

Enterprise Adoption & Engineering

From ATF to your accepted AI platform.

Abillify helps companies build, integrate and operate audit-proof AI platforms based on ATF.

Build

Target architecture, deployment on your infrastructure (Kubernetes, Docker, on-prem, EU cloud), identity and tenants.

Integrate

DMS, ERP, CRM and databases connected through governed MCP tools; documents via Extract and Outpost.

Accept

Policy as code, DPIA and record-of-processing templates, EU AI Act mapping, signed evidence for DPO and audit.

Operate

Enterprise support with SLA, updates along the releases, monitoring, red teaming and cost control.

Book an architecture call abillify.me

Productized service

Production-Ready AI Sprint

14 days · fixed price after a scoping call

You have an AI use case or a working prototype but cannot take it live because of data protection, hallucinations or IT security? In 14 days we set up an accepted ATF instance on your own infrastructure, connect your documents and systems securely via MCP, and deliver the finished audit dossier for your data protection officer.

Day 1–2 Scoping & architecture Use case, data classes, target systems, acceptance criteria. The fixed price follows.
Day 3–6 Instance on your infrastructure Runtime, Control, Search, Gate, Extract; SSO, tenants, production profile.
Day 7–10 Connect documents & systems Collections with permissions, MCP tools with approvals, a flow for your use case.
Day 11–14 Hardening & acceptance Red teaming, evals, policy, evidence keys – and the audit dossier for your DPO.

You get

An accepted ATF instance on your infrastructure
Your documents and systems connected securely via MCP
A production-ready flow for your use case
Audit dossier, DPIA and record-of-processing draft for your DPO
Handover, runbooks and training for your team

Not a 150,000-euro programme: a well-defined entry with a fixed price and a clear acceptance.

Request the sprint Book an architecture call

Who is behind it

Built in Regensburg. Verifiable from anywhere.

ATF is built and supported by Abillify Technology GmbH in Regensburg, Germany. Abillify works in payment and receivables management – an environment where evidence, data protection and approvals are everyday business. ATF grew out of production work in exactly such regulated environments.

Artur Krüger

Executive · strategy, architecture, consulting

Leads strategy, architecture and consulting at Abillify and is the author of ATF. The platform grew out of projects in regulated environments, where audit evidence, identity, data residency and approvals are preconditions for operation.

Ernst Bachmann

Technology · quality assurance & security

Leads the technical side at Abillify, with a focus on quality assurance and security.

Abillify Technology GmbH

Regensburg · Germany

Contacts in German and English, operation on your own infrastructure.

info@abillify.me Imprint

Source code public

The complete platform code is on GitHub – Elastic License 2.0, no black-box SaaS.

Signed releases

Container images and Helm chart cosign-signed, with SLSA build provenance and a CycloneDX SBOM.

35 architecture decisions

Every decision with context, alternatives and consequences – public in the repository.

Threat model & security policy

STRIDE threat model, documented limits and a reporting path for vulnerabilities.

References & pilots

Who uses ATF

We publish references only with our customers' written approval – that comes with a trust product.

We are looking for pilot partners in insurance, financial services, industry and the public sector who want to take an AI use case into production with evidence.

Become a pilot partner

FAQ

Do we need a licence?

ATF is licensed under the Elastic License 2.0: internal use, modification and self-hosting are allowed. Offering ATF to third parties as a hosted service is not. A commercial licence covers other models.

Which infrastructure do you require?

PostgreSQL with pgvector and a container platform (Kubernetes, Docker Compose or VMs). Models can be local (Ollama, vLLM, LM Studio) or EU providers.

What happens to our data during the sprint?

The instance runs on your infrastructure. We work in your environment; data leaves it only through providers you allow in the policy.

What does “accepted” mean?

Before we start we agree on acceptance criteria – e.g. eval pass rate, active controls in the posture report, verified evidence bundles. On day 14 we check against them.