We bring AI into the company, next to your people
Three specialisations: integrate AI into your systems (ERP, CRM, helpdesk) without rewrites, train machine learning models on your data, build copilots and agents that actually work every day. Security, governance and measurement included.
From the first workshop to the first AI use case live inside your systems
Average time saved on repetitive back-office and support tasks
Transparency on datasets, decisions and model cost
Synchronise data, models and people in one orbit
An animated nucleus that represents governed prompts, evaluation pipelines and real-time observability.
- Inner orbits illustrate how data signals, feature stores and prompts stay in sync.
- Peripheral nodes pulse to show co-pilots delivering insights without exposing raw data.
- Rotation speed mirrors automated evaluation cycles to keep quality measurable.
AI that delivers measurable results, not demos
Our approach is grounded: we start with the data and tools you already have, identify where AI can actually move the needle, build the first use case in production and scale it. No separate portals, no forced replacements: AI slots into real workflows with governance, transparency and human control.
We assess data quality, volume and security before any model. When needed we enrich and label it with AI-assisted workflows.
Operations, legal and compliance are involved from day one. AI nobody uses does not count: we design adoption too.
On-premise deployments, isolated VPCs or self-hosted models: when data cannot leave, we build where it lives.
Where AI actually moves the needle for your business
Three complementary paths: integrate AI into the systems you already run, train custom models on your data, and build copilots and agents that work alongside your teams.
AI integration into existing systems
We bring intelligence into the ERPs, CRMs, helpdesks, document stores and mobile apps already in use. No forced migrations: people keep working where they work today.
- SAP, Salesforce, Dynamics, Zendesk, SharePoint
- Integrated into existing interfaces
- Metering, caching and fallback included
Custom predictive models
When off-the-shelf models are not enough: we train neural networks, trees and vision models on your data to forecast, classify and recommend — with MLOps as standard.
- Forecasting, classification, vision, anomaly detection
- PyTorch, XGBoost, Vertex AI, SageMaker
- Drift monitoring and automatic retraining
Enterprise copilots and AI agents
Internal assistants that know your documents, processes and tone of voice. For sales, support, legal, HR and engineering. Agents that execute actions, not just answer.
- RAG over SharePoint, Drive, Confluence, DBs
- Guardrails against PII, prompt injection, hallucinations
- Continuous evals and automatic rollback
AI orchestration workflow
Python pipeline combining retrieval, evaluation and human-in-the-loop controls.
Where we intervene
Strategy and execution with data, product and ML expertise.
AI opportunity framing
We identify quick wins, KPIs and responsibilities across the model lifecycle.
- Use case mapping and prioritisation
- Impact assessment on processes and people
- Business case and adoption plan
Model & MLOps engineering
Data pipelines, foundation models and low-latency AI microservices.
- Fine-tuning and prompt engineering
- Feature store, monitoring and retraining
- Integration layer via APIs and webhooks
Responsibility & compliance
Ethical frameworks, explainability and human control for trusted AI.
- AI Act-ready policies
- Audit trails and model cards
- Human-in-the-loop workflows
A structured journey
Each phase reduces risk, ensures quality and accelerates time-to-value.
AI Sprint
Workshops on processes, data and metrics to select the highest-impact use case.
Output: opportunity canvas, effort and ROI estimates.
Build & orchestrate
Fast prototypes, integration into existing workflows, real-time performance monitoring.
Output: AI MVP, governed data and model pipelines.
Adopt & scale
Change management, enablement and an evolutionary roadmap driven by KPIs and feedback.
Output: operating manual, backlog of enhancements and quarterly plan.
Technologies & platforms
We choose the right stack for your context, avoiding lock-in and ensuring governance.
OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, open-source models
dbt, MLflow, Weights & Biases, Feast
LangChain, Temporal, Airflow, Prefect
Evidently AI, Arthur, custom policy engines
Connect AI with the other streams
A reliable stack to host your models
Platforms ready to run secure, scalable AI services.
AI-first experiences centred on users
Interfaces, co-pilots and workflows crafted with real insight.
AI-enabled mobile touchpoints
Extend intelligent workflows directly inside iOS and Android apps.
Let’s bring your AI to production
Book an assessment workshop with our Applied AI team.
Questions about applied AI
From integrating AI into your existing systems to custom machine learning and enterprise copilots.