Build the advantage.
Specialist programmes across model performance, physical AI, enterprise agents and the data infrastructure behind them.
Oracle enterprise integration
Extend and connect Oracle business applications within defined enterprise scope.
Oracle to PostgreSQL migration
Plan and validate database behaviour changes for a defined migration programme.
Permission aware enterprise search
Preserve document access boundaries across search and generated answers.
PLM and engineering data integration
Connect product and engineering information to enterprise collaboration and AI tasks.
Policy enforcement for agents
Apply enterprise action constraints to agent execution and approval workflows.
Power Platform automation
Develop governed business applications and automation around current workflows.
Predictive operations systems
Connect predictive outputs to maintenance, planning or operational decisions.
Preference and critique data
Collect discriminative judgements and critiques tailored to model failure modes.
Preference optimisation
Improve response selection with domain-specific preference signals and evaluation.
Private model deployment
Deploy models inside a defined enterprise boundary with operational integration.
Procurement agents
Coordinate sourcing information, purchasing records and approval stages.
Production AI operations
Establish ownership, maintenance and change control for deployed AI systems.
Prompt injection resilience
Evaluate and improve boundaries around untrusted inputs and tool actions.
Real time streaming systems
Connect continuous events to useful operational data products.
Reinforcement learning for reasoning
Advance difficult reasoning through a scoped reward and evaluation programme.
Repository engineering agents
Connect repository context, implementation and verification to engineering tasks.
Responsible AI evaluation
Evaluate behaviour against agreed use, inclusion and review criteria.
Revenue operations automation
Connect commercial data and task execution across revenue operations systems.
Reward model engineering
Create reliable scoring models for training and response evaluation.
Robot dataset curation
Organise demonstration data into usable training and held-out evaluation datasets.
Robot demonstration capture
Collect coordinated observations, poses, instructions and outcomes for robot training.
Robot imitation learning
Turn demonstrations into learnable behaviours with task-level acceptance tests.
Robot motion planning
Develop collision-aware task paths around equipment and operating constraints.
Robot offline programming
Develop and validate robot programmes in simulated workcells.
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