Digital Services · AI Agents
AI agents built for day-to-day procurement work
We design tailored AI agents that support day-to-day procurement work, improve decision-making and accelerate key processes.
Starting point
Purpose-built AI agents instead of another generic chatbot
We do not deploy repetitive chatbots. We build specialist digital micro-roles that take on the most time-consuming, analytical and repetitive tasks within a procurement team.
Each agent works in the organisation’s own context, using its procedures, templates, procurement history and contracts, with logic constrained to a verified internal knowledge base.
- The RFP & Spec Agent converts business requirements into RFP/RFI documentation, technical specifications and objective bid evaluation matrices
- The Contract Review Agent reviews draft agreements, identifies risky clauses and compares their terms with the organisation’s approved template
- Knowledge and context come from the organisation’s procedures, templates, procurement history and contracts through a RAG architecture
- Data remains within a private corporate environment, such as Azure or AWS, and is not used to train external models
- The agent performs tasks: it generates Excel files, prepares email drafts and connects to ERP systems and APIs
- Guardrails constrain the agent to the company’s verified knowledge base and minimise hallucination risk
Assessment scope
Five steps towards intelligent procurement automation
An AI agent implementation begins by selecting the right process and ends with controlled deployment, team training and the gradual scaling of the solution.
Process assessment and selection
Reviewing buyers’ day-to-day tasks and selecting one or two processes with the strongest potential for rapid return on investment.
Knowledge base preparation
Securely connecting procurement procedures, contract templates, sourcing documents and category dictionaries.
Logic configuration and calibration
Adapting the agent’s language, terminology and decision criteria to the industry, compliance requirements and organisational rules.
Testing and security
Validating outputs in a secure test environment while preserving human control through a Human-in-the-Loop model.
Deployment and scaling
Production launch, training the team to work effectively with AI, and gradually adding further modules.
AI Agents
- 01
Agents
- Workshops with key stakeholders
- Identification of process areas that can be supported by AI agents
- Design of tailored AI agents and their implementation across the organisation
- Protection of the infrastructure against data leakage
- Training on working with AI agents and using them in day-to-day tasks
Outcome
Secure automation that gives procurement teams time back
- Faster processes and time savings as repetitive analytical and documentation tasks are automated.
- Better decisions and lower costs through structured use of the organisation’s own knowledge base.
- Data security and compliance through a private environment and Human-in-the-Loop controls.
- Greater buyer satisfaction as the team can focus on work that requires judgement and business relationships.
- Scalable competitive advantage through the gradual development of further specialist AI agents.
An AI agent does not replace the buyer’s decision - it prepares recommendations and performs tasks while leaving the final choice under human control.
Let's talk about what this looks like in your organisation.