What happens to the business if we do nothing?
- Owns
- Solution architecture, LLM and agent systems
- Depth
- Full-stack delivery, data platforms
- Signature
- BI modernisation, production agent systems
HRHessam K. RadFounder & CEO
About us
Your tech & AI partner — embedded, not outsourced.
We are not just a consulting firm. We are builders, innovators and strategic partners who work from inside your organisation, aligned completely with your business objectives.
- Founded
- 2022
- Engagements
- 12
- Client retention
- 100%
- Growth
- Referral only
Our story
Founded in 2022 by engineers who were tired of watching good technology land badly.
We started DataBadger with a single, stubborn idea: to demystify and democratise the transformative power of high-end technology for every business, not just the ones with an internal platform team. The market we looked at was full of sophisticated software, data and AI solutions that were either inaccessible or badly implemented. Our whole reason for existing is to close that gap.
We are not a consulting firm. We are builders, and we embed inside your organisation to function as your internal technology department — aligned to your business objectives rather than to a statement of work. That depends on deep technical expertise, and equally on a partnership-first philosophy: collaboration, transparency, and a shared view of what success actually looks like.
We do not have a sales department. Our growth comes from our reputation and the results we deliver — which frees us to spend our time engineering, not selling.
Every client we have partnered with since our inception is still a valued collaborator. That is the metric we care about most. At DataBadger we do not just build software — we build your competitive advantage. We help you grow, and we grow with you.
How we build
Most consultancies describe their process. Ours is executable.
01
Defined roles, explicit gates
Architecture, backend, interface, data, security, QA and DevOps each own a stage, with defined gates between them. The work does not depend on who happens to be available that week.
02
Every stage leaves an artifact
A discovery brief, an architecture brief, an execution plan, a QA gate, a deployment record. Decisions are logged with the reasoning behind them and the trigger that would reopen them.
03
Enforced by machines, not convention
The methodology is a tool, not a slide. We built Olympkit — a twelve-seat engineering operating model with a defined persona and gate for every stage — and run our own engagements on it. That is why architectural boundaries are enforced in CI, and why our agent systems ship with deterministic policy gates around model output.
Core competencies
An end-to-end technology arsenal.
A comprehensive suite of services covering the entire lifecycle of a technology initiative — from initial concept through to enterprise-wide deployment, and everything that comes after.
Data platforms
Warehouses, pipelines and the reporting layer on top — owned outright rather than licensed.
- Snowflake, ClickHouse, PostgreSQL, MySQL
- dbt transformation and layered model design
- Airflow, Airbyte, Dagster, Celery, custom durable workers
- Apache Superset — embedded, customised and migrated onto
- DataHub cataloguing, ingest-log lineage
- Event-stream and xAPI ingestion, KPI generation
- Reconciliation, sanitisation, data QA
Applied AI & agents
Agents that do real work against real data, with gates that hold when the model is wrong.
- Multi-agent architectures — LangChain LCEL and LangGraph
- Durable agent execution on Temporal with human gates
- FAISS, Snowflake Cortex Search, text-to-SQL over MCP
- Model Context Protocol servers and control surfaces
- OpenAI, Anthropic, Bedrock, Gemini, local Ollama
- Evidence-linked extraction with immutable citation
- Deterministic policy engines that override model output
- LangSmith tracing and agent observability
Software engineering
Full systems built to be handed over — interface, backend, database, pipeline and the run.
- Next.js, React, TypeScript, Python/FastAPI, Java/Spring Boot
- UI/UX design and design-token pipelines
- Database design, including PostGIS geospatial
- Kubernetes, Docker, GitHub Actions, Jenkins
- OIDC, JWT, RBAC, audit logging, rate limiting
- Internationalisation, accessibility, visual regression
- Legacy modernisation and system rescue
Strategy & architecture
The analysis that happens before a technology is chosen — and occasionally instead of one.
- Business process analysis and system research
- End-to-end solution architecture
- Build-versus-buy and platform selection
- Technology and AI consulting
- Scalability and cost planning
Who you work with
Small team. Senior team.
No layer of account managers between you and the people writing the code. The founders are on the engagement, and so is everyone else.
What does this look like at ten times the load, maintained by someone who is not us?
- Owns
- Data and AI engineering at scale, platform reliability
- Depth
- ML and analytics, MLOps
- Signature
- Large-scale system delivery, technical leadership
MAMehrdad AzminCo-Founder & CTO
What would make you fire us in a year?
- Owns
- Go-to-market, partnerships, client success
- Depth
- Talent strategy, business strategy
- Signature
- Partner ecosystem and enterprise playbooks
NMNeil MayersChief Revenue Officer & Advisor
- Mehdi ChamianiLead Software Engineer
- Aidin AzabdaftariSenior Product Manager
- Sara DisvsalarSenior Project Engineer
- Mahrokh AlaeiLead QA Engineer
Start here
Start with a problem, not a brief.
Tell us what is slow, what is manual, what is stalled, or what nobody understands any more. We will tell you honestly whether it is worth building.