The tools we build with
Chosen for each problem, with no single vendor to push.
- PyTorch
- XGBoost
- LangGraph
- MCP
- Claude
- OpenAI
- Gemini
- PostgreSQL
- MongoDB
- Cassandra
- Google Cloud
- Odoo
Everything it takes to put AI to work, under one roof
Six services that work alone or together, because they share the same data.
Generative AI
Document intelligence, company search with citations, and copilots trained on your own knowledge.
Learn moreAgentic AI
Agents that complete multi-step work across your systems, with permissions, audit trails and human approval.
Learn moreClassical machine learning
Demand forecasting, predictive maintenance, churn and anomaly detection, tested against your current method.
Learn moreERP implementation
Selection, phased rollout, data migration and integration, so the whole business runs on one record.
Learn moreOdoo implementation
Configuration, custom modules, migrations and version upgrades, from an independent team.
Learn moreAI-native development
Custom software from small senior teams directing AI, so you pay for fewer hours of routine work.
Learn more
One business function, four ways to improve it
Pick a function to see what each kind of system does there.
Finance
- ERP and software
Ledgers, taxes and bank feeds in one record
- Machine learning
Flags unusual invoices and likely late payers
- Generative AI
Reads supplier bills into draft entries
- AI agents
Chases overdue invoices within your rules
Supply chain
- ERP and software
Stock, lots and reorder rules in one place
- Machine learning
Forecasts demand per product and warehouse
- Generative AI
Answers stock questions and cites the records
- AI agents
Drafts the purchase order, the buyer approves
Sales
- ERP and software
Leads, quotes and orders on one record
- Machine learning
Scores leads and predicts customer churn
- Generative AI
Drafts quotes from an emailed request
- AI agents
Follows up, then hands over when unsure
Operations
- ERP and software
Work orders, routings and quality tracked
- Machine learning
Predicts machine failures and scrap
- Generative AI
Turns shift notes into searchable reports
- AI agents
Proposes a new schedule, the planner confirms
Customer support
- ERP and software
Tickets tied to customer and order history
- Machine learning
Routes tickets by topic and urgency
- Generative AI
Answers from your own documentation
- AI agents
Issues approved refunds, escalates the rest
One team across AI, ERP and software
No handoffs between an AI vendor, an ERP vendor and a software house. The people who design it are the people who build it.
AI-native development: smaller teams, lower build costs
Senior engineers direct AI through the routine work, so your budget goes further without giving up review.
Traditional delivery
- Larger teams and more handoffs
- Routine code, tests and docs written by hand
- Long phases before you see working software
- More paid hours spent on routine work
AI-native delivery
- A small senior team directing AI
- AI drafts routine code, tests and docs, and people review them
- Working versions earlier and more often
- Fewer paid hours on routine work, so a lower build cost
Savings vary by project, and we will tell you where AI helps on yours and where it doesn’t. Gartner lists AI-native development platforms among its top trends for 2026.
- Stock is below the reorder point
check_stock("SKU-EXAMPLE") - Demand is rising, per the ML model
get_forecast("SKU-EXAMPLE") - Draft saved, nothing sent
draft_purchase_order(...) - Waiting for the buyer to approve
request_approval("buyer")
AI agents that ask before they act
Gartner expects over 40% of agentic AI projects to be cancelled by the end of 2027, citing cost, unclear value and weak risk controls. We design for all three from the first day.
- Each agent has its own limited permissions
- Every tool call is logged and readable
- A person approves anything hard to reverse
What we would build first
Systems we design and build, not a client list.
Invoice and document extraction
Bills, contracts and forms become structured data, with low-confidence fields sent to a person.
Customer support agents
Answers from your documentation, actions within set limits and a clean handover to your team.
Demand forecasting
Forecasts per product and location, feeding directly into purchasing and planning.
Predictive maintenance
Sensor and work order history turned into failure risk, before a machine stops the line.
Company knowledge search
Staff ask questions across policies and manuals, and get answers that cite their sources.
Legacy ERP migration
Off ageing systems and spreadsheets in phases, with rehearsed cutovers and tested rollbacks.
From first call to production
Small steps with a decision at each one, so you are never locked into a big bet.
Discover
We map the process, audit the data and rank use cases by value.
Prove
One use case, tested on your real data against your current method.
Deploy
Into production, inside the systems your people already use.
Run
Monitoring, retraining and the next use case on the list.
Notes from the field
Practical, sourced and written for the person who has to decide.
Have a problem worth solving? Tell us about it.
Describe the process, the systems involved and what goes wrong. Rough notes are fine.
Start the conversation