Bespoke AI agent systems for organizations navigating technical complexity
I design systems, workflows, and technical strategies that increase human leverage without reducing human agency.
Personally stewarded by Marius, amplified by a self-improving ecosystem of AI systems, knowledge infrastructure, and engineering workflows. One clear point of responsibility; unusual leverage behind it.
Anahata is not a consultancy scaled by headcount, nor a freelancer measured in hours. It is a practice - a way of working that treats engineering as the design of systems, decisions, and judgment under complexity.
The work spans AI systems architecture, knowledge architecture, technical strategy, and engineering leadership. These are not disconnected services. They are expressions of one capability: designing better technical systems for organizations operating under complexity.
Implementation is often part of the work. It is rarely the whole of the value. What clients engage is better systems, better decisions, and better technical judgment - held together by a single, accountable steward.
More leverage. Not less responsibility.
Most consulting reads as client → consultant → hours → deliverables. Anahata is built on a different model - one designed for leverage without obscuring accountability.
Steward
The steward makes trade-offs legible, carries decisions across time, and remains answerable for the system—not just a sequence of tickets.
Personally stewarded
Every engagement carries a clear point of responsibility. Nothing is outsourced to abstraction.
AI amplifies the work
AI systems expand research, synthesis, and execution - with discipline, not hype.
Knowledge compounds
Each project sharpens the infrastructure. Leverage grows over time.
Responsibility stays human
Architecture decisions ultimately carry human judgment. Always.
Situations where Anahata provides leverage.
Designing trustworthy AI systems
Moving beyond prototypes toward systems that need reliability, accountability, and real-world integration.
AI-native engineering transformation
Redesigning engineering workflows around AI without sacrificing judgment, quality, or ownership.
Knowledge architecture
For organizations whose knowledge is scattered across tools, people, documents, and tacit memory.
Technical strategy during change
For teams making high-stakes technical decisions under real uncertainty.
Engineering leadership
Architectural clarity, technical direction, and leadership through complexity.
Fractional CTO partnerships
Senior technical judgment without hiring a full-time executive.
Hands-on help to turn promising beginnings into dependable systems
Hover or focus a card to reveal its after state. Open a service to use the explicit comparison controls.
AI Safety Alignment
Digital systems rarely become unsafe through one obviously reckless decision.
AI Workflow Automation
Most AI automation begins with a useful shortcut: a prompt here, an integration there, perhaps a script connecting two tools that were never designed to work together.
App Productization
AI can turn an idea into a working iOS or macOS app remarkably quickly. That is a real achievement.
Early-Stage AI SOPs
Young businesses rarely begin with carefully designed operations. They begin with resourceful people doing whatever is necessary to move forward.
Documented not by what was built, but by how it was decided.
Long-form engineering retrospectives
Working Myself Out of the Job
Over five years and two products I drove my share of shipped code from 98% to 8% — on purpose — building a team and a platform that could ship without me on the critical path.
Wellspent
Building a digital wellbeing product meant working within platform limits without compromising user trust.
Purpose Foundation
Turning steward-ownership knowledge into an accountable conversational service and a grounded product roadmap.
Work across products, infrastructure, enterprise systems, and engineering teams
Consumer Products
Calm
Supporting a German market launch made localization an architectural concern rather than a translation task.
Keepsafe
Improving shared mobile infrastructure required treating synchronization, testability, and delivery as one system.
Developer Infrastructure
Snyk
Replacing monolithic scanning logic with plugin boundaries helped a growing organization extend ecosystem coverage.
Realm
Stewarding mobile database infrastructure showed how APIs, distribution, documentation, and support form one product.
Enterprise
Mercedes-Benz.io
Modernizing an iOS product meant connecting mobile, web, content, and deployment concerns without forcing them into one stack.
Lab1886
A reliability-sensitive internal application made state management and enterprise delivery part of the same design problem.
Early Career
accoleo
Early work on location search showed how imperfect external data becomes part of the product experience.
Modix
Internal generators and workflow tools offered an early lesson in turning recurring work into dependable leverage.
Have a difficult technical system to think through?
Bring a complex technical decision, an architecture you are unsure about, or a system that has outgrown its assumptions. The first step is a conversation, not a proposal.