AI that does the work, inside your systems.
We design, build and operate AI agents, automation and copilots that work inside your systems, are grounded in your data, and are measured by what they change.
What the line covers.
We start from a process, not a model. Whether the right answer is an agent, a retrieval assistant, a forecasting model or plain automation, it has to connect to the systems your teams already use and report against a number you care about.
We work with commercial and open models and choose per use case, based on accuracy, cost, latency and data sensitivity. The choice is documented, so you are never locked in by a decision you didn’t see being made.
AI strategy
A plain answer to where AI pays off in your operation, where it doesn't, and what to build first.
- Process and data readiness review
- Use-case scoring by value, risk and effort
- Build-versus-buy recommendations
- A sequenced, costed roadmap
AI agents
Agents that plan, call your tools and finish multi-step work across systems, with approval gates where they matter.
- Tool and API design for agent access
- Multi-step workflow orchestration
- Human approval and escalation paths
- Evaluation suites and run logs
Intelligent automation
Repetitive back-office work removed by combining language models with conventional automation and RPA.
- Process mining and task capture
- Document intake and classification
- Exception handling designed in, not bolted on
- Before-and-after effort measurement
Conversational AI
Support, sales and internal assistants on web, chat and voice that answer from your knowledge, not guesswork.
- Retrieval over your documentation and tickets
- Hand-off to human agents with full context
- Channel integration: web, WhatsApp, Teams, Slack
- Deflection and satisfaction tracking
Document & vision AI
Invoices, contracts, forms and images turned into structured, validated data your systems can use.
- Extraction with field-level confidence
- Validation against master data
- Visual inspection for physical processes
- Review queues for low-confidence items
Predictive ML
Forecasting, scoring and anomaly detection wired into the decisions your teams already make.
- Demand and cash-flow forecasting
- Risk and propensity scoring
- Anomaly detection on transactions
- Model monitoring and retraining
Custom applications
Web and mobile products with AI built into the core, from first prototype to production.
- Product discovery and UX
- Web and mobile engineering
- Cloud infrastructure and CI/CD
- Security review before launch
What we build with.
Technologies we work with day to day. We are not affiliated with or endorsed by these vendors; we choose whatever fits your stack.
- Models
- OpenAI, Anthropic Claude, Google Gemini, Llama and other open-weight models
- Cloud AI platforms
- Azure AI Foundry, AWS Bedrock, Google Vertex AI, OCI Generative AI
- Retrieval & data
- PostgreSQL with pgvector, Elasticsearch, Snowflake, Databricks
- Engineering
- Python, TypeScript, LangGraph, Kubernetes and serverless
Change at Oracle ERP.
These interchanges need both practices. They are where one partner saves you a hand-over.
- AE
Copilots on ERP data
Assistants that answer finance, procurement and HR questions directly from your Oracle data, respecting the same roles and permissions.
- AE
Finance operations automation
Invoice matching, reconciliations and close tasks handled by agents that post into Oracle, with every action logged and reviewable.
- AE
Supply-chain signals
Forecasts and anomaly alerts generated from ERP transactions and pushed back into the planning screens your teams already use.
Have a process in mind?
Send a few lines about what you are trying to fix. A consultant, not a sales bot, replies within one working day.