Agence web / IT & innovation
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AI • AGENTS • COPILOTS

Useful AI agents, integrated and under control

We turn AI into operational impact: reliable search (RAG), tool-assisted automations, integrations (CRM/ERP) and measurable quality (sources, traceability, validations).

Estimer votre projet → No commitment • 30 min • Clear answer

Outcome-driven AI use cases

We start from a concrete need (support, sales ops, back-office) and define success criteria, limits and guardrails.

use casescopeROIsourcestraceabilityvalidationmetricsiterationsrun

RAG: reliable answers on your data

Assistants on documents/tickets/contracts: we reduce hallucinations with sources, search and controlled access.

docsticketsFAQindexingrelevancecitationspermissionsconfidentialityGDPR

Tool-using agents & integrations

Agents act through APIs and workflows: CRM/ERP, messaging, calendars, back-office. Everything is traceable and operable.

toolsactionscontrolsAPIswebhooksworkflowslogsalertssupervision
USE CASES

What does your AI need look like?

One page per use case = clearer message, better qualification, faster decisions.

Clarify your AI project in 30 minutes

We secure the use case, the data, the required reliability, and the integration (CRM/ERP/workflows). You leave with an action plan and quick wins.

Faster decisions

Use case, scope, data: we settle what matters.

Less risk

Quality, sources, guardrails, compliance: we avoid “black-box” AI.

Concrete plan

POC → V1 → production, with metrics and operations.

Estimer votre projet → No commitment • 30 min • Clear answer
Why Antesy?

Useful AI under control: reliability, integration, operations

We focus on operational value: sourced answers, traceable actions, guardrails and steering.

FAQ

AI & agents: FAQ

Use cases, RAG, reliability, integration, security and GDPR compliance.

What budget for an AI project (agents, RAG, support chatbot, automations)?

Budget depends on scope, integrations (CRM, ticketing like Zendesk/Intercom, SharePoint/Drive, SSO, APIs) and quality requirements (performance, security, monitoring). After a diagnostic, we provide a realistic range and a delivery plan. Keywords: AI agent, RAG, support chatbot, enterprise LLM, automation, knowledge base, security.

How long does it take to start an AI project (agents, RAG, support chatbot, automations)?

We usually start with a diagnostic (30–45 min) then a short discovery (1–2 weeks): goals, users, risks, architecture, MVP backlog. Then we deliver through iterations (sprints) with clear milestones.

What do you deliver for an AI project (agents, RAG, support chatbot, automations)?

A usable product: UX/journeys, development, targeted tests, deployment, essential documentation, and a maintainable base (code quality + conventions). Optional: monitoring, analytics and runbook.

What should we prepare before starting an AI project (agents, RAG, support chatbot, automations)?

Business goal, target users, constraints (GDPR/security), content/sources, and systems to connect (CRM, ticketing, SharePoint/Drive, SSO, APIs). If you don’t have everything, we structure it during discovery.

Who is an AI project most relevant for?

Typically: support teams, ops teams, business teams, companies seeking measurable ROI. It’s relevant if you want industrial-grade quality (security, governance, monitoring).

NEXT STEP
Ready to build?

Estimate your project in 2 minutes — or book a free 30-min diagnostic.