Data, Analytics & AI
One number everyone trusts, then models worth acting on.
- A single warehouse every team reports from
- Dashboards that answer the questions leadership actually asks
- Models evaluated against a baseline before anything ships
- AI features with cost, latency and accuracy monitored in production
Why companies bring us in
Most AI projects fail on data, not models. Archanix starts by making your numbers consistent — one pipeline, one warehouse, one definition of revenue — and only then builds the forecasting, scoring or AI assistants that depend on them being right.
- A single warehouse every team reports from
- Dashboards that answer the questions leadership actually asks
- Models evaluated against a baseline before anything ships
- AI features with cost, latency and accuracy monitored in production
The work, itemised
Everything below is part of a data & ai engagement. We scope which parts you actually need before quoting.
Data engineering
Ingestion from your applications, CRM, ad platforms and spreadsheets into a warehouse, with tests that fail loudly when a source breaks.
Business intelligence
Dashboards in Power BI, Looker Studio or Metabase built around decisions rather than every chart the tool can draw.
Machine learning
Forecasting, churn and propensity scoring, recommendation and anomaly detection — always benchmarked against the simple approach first.
LLM applications
Retrieval-augmented assistants, document extraction and support automation grounded in your own content, with evaluation sets and guardrails.
MLOps
Versioned datasets, reproducible training, deployment pipelines and drift monitoring so models keep working after launch.
Data governance
Lineage, access control, retention and personal-data handling that stands up to an audit.
How the engagement runs
Every stage ends with something you can read, click or decide on — never a status update alone.
- 01
Audit
We trace where each number comes from today and document why two reports disagree.
- 02
Model
A warehouse schema and metric definitions agreed in writing with the teams who own them.
- 03
Pipeline
Automated, tested ingestion and transformation with alerting when a source changes shape.
- 04
Prove
A pilot model or assistant evaluated against a baseline on your real data before it goes near production.
- 05
Operate
Monitoring for accuracy, cost and drift, with a retraining schedule and a rollback path.
What we build with
We pick tools for how long they will be maintainable, not for how new they are. Where you already have a stack, we work in it rather than arguing for a migration you did not ask for.
- Python
- dbt
- Airflow
- BigQuery
- Snowflake
- PostgreSQL
- Power BI
- Metabase
- PyTorch
- LangChain
- OpenAI
- Claude
Data & AI by industry
The same capability behaves differently depending on what the business does. These are the sectors where this service comes up most.
Sometimes. Document extraction, support deflection and forecasting pay back quickly at modest scale. We size the opportunity in discovery and will tell you plainly when a dashboard would serve you better than a model.
Yes. Retrieval-augmented generation keeps answers grounded in your own content with citations, and we build an evaluation set so accuracy is measured rather than assumed.
In your own cloud account under your control. Where a third-party model provider is involved we use options with no training on your data and document exactly what leaves your boundary.
A first warehouse and executive dashboard on your priority metrics usually lands within six to eight weeks.
Services that pair with this one
Automation & Integration
Workflow automation and system integration that connects the tools you already pay for, removing the manual re-entry that quietly consumes whole roles.
View serviceCloud & DevOps
Cloud migration, infrastructure as code, CI/CD pipelines and cost optimisation on AWS, Azure and Google Cloud — with the bill reviewed every month.
View serviceCustom Software Development
Bespoke platforms, internal tools and customer-facing products engineered end to end. We ship in fortnightly increments so you see working software early, not a demo at the end.
View serviceGet a written quote
for data & ai
Tell us the situation and the deadline. You get a scope, a price and a start date — not a discovery call that turns into three.