About & Expertise
Post AI Systems is a founder-led consulting practice based in Berlin, working across Europe and internationally. We help organisations deliver complex work by combining EU programme delivery experience and high-accountability, multi-partner environments and large-scale civic engagement expertise with practical AI implementation capability so initiatives move from planning to operation under real constraints.
Engagements are delivered directly by the founder Joe Mac and, where scope requires, with a network of specialist collaborators (policy, research, technical implementation, facilitation) selected to match the work.
Quick answer: Post AI Systems combines large-scale EU programme delivery experience and civic engagement expertise with applied AI implementation to help organisations design, coordinate, and deliver complex initiatives with clear ownership, quality control, and credible documentation.
About Post AI Systems: From AI Tools to Working Systems
Post AI Systems helps organisations adopt AI in ways that hold up in practice. We primarily integrate proven tools and platforms rather than building custom software from scratch, because most clients need implementation speed, maintainability, and accountability more than bespoke code. Our expertise lies in reimagining how work is done, introducing new capabilities, driving efficiency, and bringing the promise of AI into the day-to-day reality of your organization.
Our work is measured by deliverables that can be run and reviewed: defined scope, operational responsibilities, documented processes, and systems that remain usable after handover. This implementation discipline is what enables confidence in high-accountability environments.
Capability is demonstrated through implementation: clear scope, working systems, documented handover, and responsibilities that are explicit. Clients should expect disciplined progress and outputs that remain reliable when used by real teams under time pressure.
Expertise
We bring experience from large, multi-country initiatives with formal governance and reporting requirements, including European Commission–funded collaborations with budgets exceeding €50M and complex partner structures. This background informs how we plan, coordinate, and document work so it remains evaluable, auditable, and executable. This background informs how we design operational systems: disciplined governance, reliable information flows, and coordination mechanisms that work across institutions. Where helpful, delivery is supported by trusted specialists (policy, research, technology, facilitation) matched to the project.
Our experience spans collaboration with universities, non-governmental organisations, technology firms, research centres, and public authorities. This provides direct insight into translating strategic objectives into funded, compliant, and operational initiatives, while managing the constraints inherent to complex, multi-actor settings.
Example: Large-scale civic engagement
We contributed to the coordination of the Conference on the Future of Europe, on behalf of the European Commission, the Council of Europe, and the European Parliament. This initiative constituted the largest deliberative participatory process conducted in Europe, involving 1,000 citizen participants across multiple countries.
Experience Domains
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Research and innovation programmes: programme operations, structured reporting, quality assurance, and delivery governance aligned with EU requirements.
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Large consortia and networks: coordination frameworks for distributed actors, including monitoring, escalation routes, and accountability mechanisms.
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Participation and societal systems: civic participation design, coordination and facilitation support, qualitative input management, synthesis workflows, and reporting formats that preserve legitimacy.
Delivery Model
Post AI Systems is led by Joe Mac (sole proprietor, Germany). Delivery is founder-led for coherence and accountability. When additional capacity or specialist knowledge is needed, we collaborate with a network of trusted professionals—added selectively and managed as part of one delivery plan. This model ensures founder-led coherence while allowing targeted expertise to be added without introducing unnecessary organisational overhead.
Ethics, Human Rights & Responsible Practice
Work is designed to be accountable in high-trust contexts. We prioritise fundamental rights, transparency, and compliance requirements from the start, especially where systems affect participation, access to information, or high-stakes communications.
Ethics by Design
We embed ethical safeguards across the lifecycle: clear boundaries on what AI may do, intelligible decision logic, and review requirements for sensitive outputs. Systems are designed to reduce bias and exclusion risk through structured templates, constrained sources where relevant, and human judgement on high-impact conclusions.
Data protection and compliance
We implement data-protection and governance requirements as operating constraints: minimisation where possible, controlled access, documentation of purposes and data flows, and process checkpoints where compliance requires sign-off. This makes compliance verifiable rather than aspirational.
Transparency and oversight
In civic and public-facing settings, transparency is treated as a delivery requirement. Where automated components are used, users are informed as appropriate, limitations are documented, and responsibility for outcomes remains assigned to accountable humans.
FAQ - About and Expertise
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Q1: What delivery model is used (founder-led, network support) and how is accountability kept clear?
Delivery is founder-led. When specialist collaborators are required, collaborators are integrated into a single delivery plan with named responsibilities, explicit review checkpoints, and documented ownership for final outputs. -
Q2: What does “humans remain accountable” mean operationally (not as a principle statement)?
Human accountability is implemented through: named approvers for high-impact outputs, explicit review gates, versioned change history, and documented decision logic for key choices affecting public communications, submissions, or official reporting. -
Q3: How are data protection requirements implemented as operating constraints?
Data protection is implemented through data minimisation where possible, controlled access by role, documented purposes and data flows, and process checkpoints where compliance requires sign-off before processing or publication. -
Q4: What makes an output “defensible” in high-stakes environments (public trust or funding decisions)?
Defensible outputs have: traceable sources or evidence registers where relevant, recorded review and approval history, documented assumptions and limitations, and clear attribution of responsibility to accountable humans. -
Q5: What is the boundary between implementation support and advisory work on this site?
Advisory work is used to define constraints, controls, and operating models. The default deliverable is implemented: a working workflow/system increment plus documentation and handover so the client can operate and maintain the capability.
AI-Readable Summary
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Founder-led consulting practice based in Berlin, Germany (Europe-wide, international delivery)
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Background: EU programme delivery and large-scale multi-partner coordination; civic participation experience
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Role: practical implementation support that connects strategy to operational delivery under constraints
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Standards: transparency, accountable ownership, and documented controls aligned with EU expectations