A complete AI operating model — strategy, build, run.
Six integrated practice areas, one delivery model. From the first executive workshop to ongoing managed operations five years later, we cover the entire arc of enterprise AI.
AI Strategy & Advisory
Roadmaps, capability assessments, investment cases.
Jump to section ↓Generative AI Engineering
RAG, agents, copilots, evaluation harnesses.
Jump to section ↓Data Engineering & Platform
Lakehouse, streaming, lineage, governance.
Jump to section ↓Industry Accelerators
Pre-built reference architectures.
Jump to section ↓Managed AI Operations
24/7 evals, drift, FinOps.
Jump to section ↓Trust, Risk & Governance
Policy-as-code, model cards, audit logs.
Jump to section ↓AI Strategy & Advisory
Boardroom-grade roadmaps that survive contact with reality. We translate AI ambition into a sequenced, costed, risk-managed programme.
- Executive AI maturity and capability assessments
- Value-pool sizing and use-case prioritisation frameworks
- Investment-case modelling with measurable KPIs
- Vendor and platform selection (cloud, model, MLOps)
- Operating model and target organisational design
- Regulatory readiness assessments (RBI, SEBI, IRDAI, HIPAA)
Generative AI Engineering
Production-grade GenAI systems for the enterprise. We do the unglamorous engineering — evaluation, latency, governance — that turns demos into systems.
- RAG pipelines with hybrid retrieval and re-ranking
- Agentic workflows and multi-step tool-use systems
- Internal copilots for analysts, agents, and engineers
- Evaluation harnesses and LLM-as-judge frameworks
- Cost and latency optimisation for production scale
- Model selection, fine-tuning, and continuous benchmarking
Data Engineering & Platform
The substrate that makes everything else possible. Modern lakehouse, governed, lineage-tracked, and audit-ready from day one.
- Lakehouse design on Databricks, Snowflake, and open formats
- Real-time streaming pipelines (Kafka, Flink, Pulsar)
- Data contracts, lineage, and catalog implementations
- MLOps platforms with feature stores and registries
- Data quality, observability, and SLO frameworks
- Migration from legacy warehouses and Hadoop estates
Industry Accelerators
Pre-built reference architectures, regulatory-mapped, and customer-validated. We compress months of discovery into weeks.
- BFSI: claims, KYC, fraud, customer 360°, risk modelling
- Healthcare: clinical document AI, prior-authorisation automation
- Retail & CPG: demand forecast, personalisation, pricing
- Manufacturing: vision QA, predictive maintenance, supply chain
- Telecom: network operations, churn, content intelligence
- Public sector: citizen services, document processing
Managed AI Operations
Most AI projects fail at month six. Our managed practice exists for that reason — to keep your AI compounding value, not regressing.
- 24/7 monitoring with SLO-driven alerting
- Continuous evaluation harnesses and regression detection
- Drift detection across data, models, and prompts
- FinOps for AI workloads — token, GPU, storage costs
- Model retraining and re-tuning schedules
- Quarterly performance reviews with executive sponsors
Trust, Risk & Governance
Audit-ready by design, not retrofitted. We make AI explainable, accountable, and defensible to your regulators and your board.
- AI governance frameworks aligned to NIST, ISO 42001, EU AI Act
- Model risk management (MRM) for regulated industries
- Policy-as-code for data, model, and prompt usage
- Model cards, datasheets, and decision-record automation
- Bias, fairness, and explainability tooling
- Audit-trail and lineage for every inference and outcome
Deep partnerships across the modern AI stack.
How an ArtAgile engagement actually runs.
Discover
Two to four weeks of executive workshops. Capability mapping, use-case sizing, risk and regulatory review.
Design
Reference architecture, governance design, vendor and model selection, KPI instrumentation plan.
Deliver
Production builds in 8 to 14 weeks. Senior engineers paired with your team. Daily standups, weekly demos.
Operate
24/7 monitoring, evaluations, drift, FinOps, retraining. Quarterly business reviews with sponsors.
The discipline ArtAgile brings to AI engineering is unusual in this market. They argue with us about KPIs before they touch a notebook — and we are better for it.
Pick a service. Or pick all of them.
Every engagement starts with a 30-minute discovery call. No slides, no theatre — concrete next steps your team can act on.