Services
Two services. One outcome. We validate your use-case in 4–6 weeks, then ship production agentic systems that move the numbers. Enterprise-grade. Delivered by one accountable team.
The two services
Two distinct services. One accountable team across both. Most engagements start with AI Strategy and continue into production. You can also enter at either step.
(AI Discovery)
Validate the use-case before you build it.
A 4–6 week structured engagement that runs two parallel streams — technical feasibility and strategic assessment — and ends with a prioritised roadmap, clickable prototypes, and an ROI model the client already trusts.
Realisation rate of Discovery use-cases in production
(Production systems)
Ship the system to production.
Full build and deployment of custom AI systems into enterprise environments. Most are agentic — autonomous agents, multi-agent orchestration, workflow automation — designed around your specific processes, data, and compliance requirements.
Production AI systems deployed across enterprise environments
Who we build for
We build for companies with revenue, complexity, and a need to differentiate through AI.
Finance, healthcare, telco, manufacturing, insurance, CX. Looking for production AI that survives compliance, integration, and scale constraints.
Companies with revenue, complexity, and the need to differentiate through AI — but not yet the in-house engineering depth to ship it.
Building deep AI tech (inference, multi-agent systems, foundation models) and need a team that can ship production engineering at startup speed.
P&L impact
Every use-case we ship comes with an ROI model. Every production deployment is measured against the P&L line it was built to move. These are the outcomes — not the demos.
$3B+ business value created across 100+ production deployments in finance, healthcare, manufacturing, insurance, CX, and more.
See all case studiesEngagement shapes
Most enterprises start with Discovery. You can also skip ahead or engage on a retainer.
Most common for enterprises new to AI. Discovery validates the use-case in 4–6 weeks. Production engagement builds and ships it.
Use-case is already validated. Skip Discovery and go straight to build and deployment.
Retained engagement for continuous capability building once the first system is live and operational.
The architecture
Every engagement enters through AI Strategy, exits through a Custom Agentic AI Platform. Underneath: three capability pillars that combine into the system you actually need.
Step 1 — Entry
(AI Discovery)
4–6 weeks. Two parallel streams: technical feasibility + strategic assessment. Ends with a prioritised roadmap and clickable prototypes of the top use-cases.
Step 2 — Production
Full build and deployment of production AI systems. Most are agentic — autonomous agents, multi-agent orchestration, workflow automation — designed around your processes, data, and compliance requirements.
Agentic AI
Autonomous agents that act, not just answer
Multimodal AI
Vision, audio, documents — cross-modal intelligence
Predictive AI
Forecasting, detection, and optimisation at scale
Underneath
Proven modules, integration patterns, agent architectures, and AI-native UX components — accumulated across 100+ deployments. Your system is bespoke. The foundation underneath is battle-tested.
The Sudolabs AI Platform
Every agentic system we build leverages proven modules, integration patterns, and agent architectures refined across 100+ enterprise deployments. Your system is bespoke. The foundation underneath is battle-tested.
That's how we compress 12-month builds into 3 — without cutting corners.
Most AI services firms operate at 1–2 layers. Production systems require all 4.
