Chatbots answer. Our agents close the loop.
An AI agent is autonomous AI software that completes a task end-to-end inside your systems, not just answers a question. We build agents that plug into your existing stack, take real actions, and ship to production in months, not a multi-year platform bet.
90% of IT leaders feel urgency to adopt AI agents, but fewer than half can explain what separates an agent from a chatbot. (Salesforce, 2025)
Most pilots stall. The ones that ship pay back fast.
What's the difference between an AI agent and a chatbot?
A chatbot answers questions with text. An AI agent takes the next step: it makes a decision within set limits and completes the task in your systems, without a human doing each step manually.
Tells someone their order status
Processes the return, end to end
IA, Données et Analyse
We turn your data into decisions: architecture, BI, and analytics that surface what's happening and what to do next.
See AI, Data & Analytics →AI Agents & Generative AI : this page
We build the agents and generative applications that act on those decisions automatically, in production, on your existing systems.
Not sure your data is ready? Take the AI Readiness Assessment →Built for how your industry runs
Same agent architecture everywhere: the documents, systems, and rules it works inside change per vertical. Browse the one closest to you.
Four kinds of agents, one architecture
Workflow Automation Agents
Multi-step back-office processing (invoice and document handling, approvals, settlements) run end to end, not just flagged for review, the same category of field service agents for utilities providers use for dispatch and scheduling.
Customer-Facing Copilots
Support agents that resolve, not just deflect.
Internal Knowledge Agents
Search, synthesize, and act across your internal systems and data.
Proposal & RFP Drafting Agents
Draft first-pass responses from your knowledge base and past work.
RUNS ON THE PLATFORMS YOU ALREADY USE
Get your AI Agent Readiness Score
Eight questions across four categories: process, data, ownership, and governance. Answer two here to see how it works, then take the full assessment for your score, category breakdown, and the Decision Guide sent to your inbox.
Start the full diagnostic →Verified results, not projections
Selected work across agents, automation, and applied ML: real, shipped projects, not deck-only claims. Only the featured tile below carries a published metric; the rest link straight to the write-up.
AI-Driven Digital Signage & Audience Intelligence
Accelerating Workflow Migration with a BPMN-to-Conductor Converter
Elevating Customer Experience: AI-Enabled Chatbot
Transforming Dietary Habits with AI-Powered Coaching
Revolutionizing Waste Management with AI-Powered Solutions
Innovating Person Detection: ML Advancements in Identification
AI-Driven Face Recognition Automates Payroll & Attendance
Automatisation des flux de travail pour une chaîne de restaurants leader au Japon
Ready to see where you stand?
Take the 4-category readiness diagnostic for a quantified score and a tailored guide, or talk to us directly: either way, you leave with a specific answer, not a generic pitch.
Questions we get before a first call
A chatbot answers questions with text. An AI agent takes the next step: it makes a decision within set limits and completes the task in your systems, without a human doing each step manually.
Yes, customer-facing copilots are one of our core agent categories: agents that resolve real requests directly in your systems, escalate what genuinely needs a human, and hand off with full context instead of making the customer start over.
Audit logging that tracks every action, an escalation path for anything outside its defined limits, and a tested rollback plan: the same controls you'd expect from a new hire with system access, not fewer.
It depends on scope: a single, well-defined workflow gets to a working agent fastest. Scoping that first workflow is what turns a guess into a real timeline.
On your existing stack by default: the agent connects into your current tools; it isn't a new system to migrate.
Yes, that service turns your data into decisions. This one builds the agent that acts on those decisions automatically. Learn more about IA, Données et Analyse.
MIT's 2025 GenAI Divide report found that AI tools bought from specialist vendors or built through partnerships succeeded about 67% of the time, at least twice as often as internal builds: the Decision Guide on this page walks through why, specific to your workflow.
It depends mainly on three things: how many systems the agent needs to connect to, how much judgment versus fixed rules the task requires, and whether it's one workflow or several. Scoping a single well-defined workflow first is the way to get an accurate number instead of a guess. A free AI readiness assessment is a good first step.
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