Agents that run your workflows, not demos

Agent, copilot, chatbot, automation: telling them apart

Term	What it is	When to use it
Chatbot	Answers questions	First-line support, FAQ
Copilot	Assists inside a tool (suggests, drafts, summarises)	Augmenting an employee without changing how they work
Agent	Reasons and carries out a sequence of actions	Automating a complete workflow, with intermediate decisions
Automation (rules)	Executes fixed rules	Stable, deterministic tasks that need no judgement

Most real needs combine these building blocks. A common mistake is to want an autonomous agent where simple automation would do: more expensive, riskier, less reliable.

Where an agent creates value

• Handling incoming requests: sorting, qualifying, routing to the right person, with an assisted reply.
• Document sequences: extracting, checking, filling in, passing on, wherever a person today copies and pastes between systems, the territory of document analysis.
• Business copilots integrated with your existing tools (CRM, ERP, support): summaries, contextual alerts, drafts.
• Research and analysis: working through large volumes, surfacing what matters, preparing a decision that a person makes, often built on RAG.

Making an agent reliable in production

An agent that impresses in a demo and an agent that holds up in production are two different things. Our deployments include guardrails (a bounded scope of action, human validations at sensitive points), continuous evaluation, production monitoring, and clear governance (who can do what, traceability). Without this industrialisation layer, an agent becomes a risk rather than an asset: this is exactly what blocks the move from POC to production.

Our approach

We start from the workflow, not the technology: diagnose where time is lost, redesign the sequence, build the right agent or copilot, deploy it with oversight, iterate on the next workflows, then hand over. An agent is not an end in itself: it exists to remove a friction and put the fix into production.