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Capabilities

01

Chatbots

Intelligent conversational assistants for customer service and sales. Available 24/7, they answer common questions, qualify leads and reduce the workload on your teams.

02

Automation

Automate repetitive tasks through machine learning. Document classification, data extraction, smart workflows: save hours every week on manual processes.

03

Data analysis

Extract insights and predictions from your business data. Identify trends, anticipate customer behavior and make informed decisions with AI-powered dashboards.

04

API integration

Connect to OpenAI, Claude, Mistral and specialized AI APIs. We integrate the best models on the market into your applications, with architecture designed to scale.

Audience

Who is this
service for?

You have repetitive tasks, untapped data or an overwhelmed support team, AI delivers measurable results, not hype.

  • SMB that wants a 24/7 FAQ chatbot to deflect support tickets without hiring extra staff
  • Team buried in internal docs (wikis, PDFs, Confluence) that wants to query its knowledge base in plain language
  • Operations team spending hours manually extracting, sorting or classifying data from emails and documents
  • SaaS product or startup adding a conversational AI feature without rebuilding from scratch
Process

How it
works.

We identify the processes that AI can optimize in your business. After a POC to validate the approach, we develop and integrate the solution into your existing tools. Training and documentation are included to ensure adoption.

Why us

What makes the
difference.

Pragmatic AI solutions, not tech for tech's sake. We measure the ROI of each integration and ensure AI delivers concrete value to your team.

FAQ

Frequently asked questions.

OpenAI (GPT-4o) and Anthropic (Claude) cover 90% of use cases well: reliable APIs, strong performance and predictable inference costs that scale with your usage volume. A self-hosted open-source model (Mistral, LLaMA) makes sense when data sensitivity prohibits third-party processing, or when inference volume makes API costs unsustainable. We assess the right architecture at kickoff, there is no one-size-fits-all answer.
Cost depends on complexity: a FAQ chatbot with RAG on a small corpus, a business assistant with multiple integrations (CRM, Slack, internal API) and an autonomous agent on internal workflows are very different projects. LLM API operating costs also factor in, varying with your usage volume. Every project is quoted after a free scoping call, get an estimate within 12 hours.
Yes, when the architecture is set up correctly. Both OpenAI and Anthropic offer API modes that do not use your data to retrain their models. For highly sensitive data, we can deploy an open-source model (Mistral, LLaMA) inside your own infrastructure or private cloud, your data never leaves your environment. We document the data flow and processing steps so your DPO can validate GDPR compliance without friction.
High-ROI use cases include: automated support ticket responses (40–60% deflection of manual handling), structured data extraction from PDFs or emails (hours saved per week), document classification and triage, and meeting or report summarization. RAG (retrieval-augmented generation) lets your team query hundreds of pages of internal documentation in plain English. We always start with a 2–3 week proof of concept to validate value before any production deployment.
That is exactly our approach. We connect AI assistants to your stack via APIs: Slack, HubSpot, Salesforce, Notion, Intercom, your web application or any tool with an API. Workflow automation layers (Make, n8n, Zapier or custom code) allow a chatbot conversation to trigger a CRM action, or feed an assistant from your Confluence space. Post-deployment maintenance and updates are covered in our ongoing support plans.

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