AI Strategy & Discovery
Roadmaps grounded in your data, your constraints, and the technology that actually works. No buzzword bingo.
- AI Maturity Assessment
- Organization Training Plan
- Use-case prioritization
- Buy vs. Build Analysis
- ROI & risk modeling
Now booking Q3 2026 engagements
Production-grade AI & ML
engineered for the real world.
We are a senior AI & Machine Learning consultancy. From data foundations to LLM-powered products, we partner with teams to architect, build, and ship systems that perform — at scale, in production, with measurable ROI.
/ tech agnosticism
We meet your stack where it already lives.
Cloud, warehouse, orchestrator, LLM — we work with what you have. That independence lets us recommend the most performant, cost-efficient solution for the business problem, instead of bending the problem to fit a preferred tool.
+ many more — if it has an API or a driver, we can plug into it.
/ approach
A predictable path from signal to system.
Five phases, one continuous loop of value creation. Hover any phase to see the activities, deliverables, and value it adds — and how each iteration compounds.
expertdata · journey.flow
iterating Data and evidence driven. We hold ourselves to the scientific method so every conclusion is defensible and backed by data — and balancing that technical rigor with effective, on-time delivery is what's in our DNA.
iterate experiment optimize
Hover any phase to see activities, deliverables, and value added.
Activities
Deliverables
/ services
Everything you need to take AI from idea to production.
Six focused practices, one senior team. We embed alongside your engineers — not above them — and leave you with systems your team can own and extend.
Most requested
LLM & Generative AI
RAG, agents, fine-tuning, and evaluation pipelines. We build LLM systems that are reliable, observable, and cost-aware.
- Agentic workflows
- Retrieval & embeddings
- Eval harnesses + guardrails
Data Engineering
Modern stack pipelines, lakehouses, and feature stores — the unglamorous foundation that makes everything else possible.
- ELT & streaming
- Lakehouse architecture
- Quality & lineage
ML Engineering
Custom models, rigorous training pipelines, and the boring discipline of reproducibility. From research notebook to production binary.
- Recommender systems
- Forecasting & CV
- Experimentation platforms
MLOps & Platform
CI/CD for models, drift monitoring, cost dashboards. The infrastructure that lets your team ship models like software.
- Model registry & serving
- Observability & drift
- FinOps for AI workloads
Staff Augmentation
Senior engineers and ML scientists embedded into your team — three engagement schemas to fit how you run.
- Self-managed FTEs
- Managed FTEs
- Project & team management
/ selected work
Outcomes, not demos.
A small sample of recent engagements. Names changed where confidentiality demands it; the numbers are real.
Extending the capabilities to explore, analyze and derive conclusions from data.
Built an agentic system that support business users in exploring and analyzing data, and taking actions on it, including their internal data knowledge base.
87% auto-resolution
4.2× faster TTI
$1.8M annualized savings
Built a recommender stack and lifted replacement rate saving 3M € in 3 months.
Two-tower retrieval + cross-encoder ranking, served at sub-100ms p99. Shipped with a retraining strategy and end-to-end observability and alerting.
20 RPS
50ms p99 latency
70+ countries enabled
Deployed a CV pipeline that catches defects in coffee beans.
Co-designed with coffee producers and experts to profile coffee quality and assess production value. It runs on edge devices used by the farmers the production farms.
91% recall
Sub-1s p99 latency
11 regions in production
Built a data platform that reduced warehouse costs by 64% and integrated multiple sources for unified analytics.
Audited query patterns, refactored data models, and introduced a medallion materialization strategy. Paired with the data team for faster iteration and deployment.
−64% warehouse cost
2.1× dashboard speed
0 regressions
$5M+ € in measurable client outcomes
3 Time zones covered by our team in multiple geographies.
100% of projects shipped to production
12 yrs average team experience
/ about
A multidisciplinary team built to ship high-end solutions.
Data Science, ML, Data, Software, and Platform engineers — plus seasoned Project and Product leads — collaborating under one delivery org. Years of production experience across regulated and high-scale domains mean the right specialists land on your problem from day one.
- Cross-functional pods — research, engineering, and product moving together.
- Flexible scale: spin up a focused 2-person spike or a full 20+ delivery team.
- Fixed-scope phases with weekly demos.
- Code, infrastructure, and docs you fully own.
- A standing 90-day post-launch warranty.
SYSTEM ONLINE UTC --:--
median experience12 years
tz coverageLATAM · US · EU
scalefrom 1 → 20+ engineers
practices
Data ScienceMachine Learning EngineeringData EngineeringSoftware EngineeringProject ManagementProduct Management
$ expertdata --status