Enterprise AI assistants
Assistants that answer with your company's information, for customers on your website or for internal teams.
Artificial intelligence
Artificial intelligence solutions for businesses
We take generative AI from experiment to operations: assistants, intelligent search over your documents, automated information processing and agents integrated with your corporate systems.
Artificial intelligence creates value when it solves a concrete business problem: answering customer questions, extracting data from documents, classifying requests or finding information scattered across thousands of files. We start by identifying the highest-return use cases and validate their feasibility with your own data before scaling.
We build solutions with large language models (LLMs), RAG (retrieval-augmented generation), OCR and AI agents, integrated with your ERP, CRM and databases. We take care of data privacy, model usage costs and measuring the quality of the answers.
What the service includes
RAG over your documents
Search and answers over manuals, contracts, regulations and knowledge bases, citing their sources.
Document processing and OCR
Automatic data extraction from invoices, forms and scanned documents.
Agents and automation
AI agents that run multi-step tasks connected to your systems and APIs.
AI-powered data analysis
Classification, pattern detection and text analytics to support decision-making.
Language model integration
Secure connection of LLMs with your ERP, CRM and databases, with access and cost control.
Benefits for your business
Higher productivity
Automate repetitive tasks and free your team for higher-value work.
Answers from your data
The AI answers with your company's information, not generic responses.
Privacy and control
Architectures that protect sensitive information and log usage.
Measurable results
Quality and cost metrics to decide, with data, when to scale.
Technologies we use
- LLMs
- RAG
- OCR
- AI Agents
- Automation
How we work
- 01
Diagnosis
We analyze your architecture, processes and business goals to identify risks and opportunities.
- 02
Solution design
We design an architecture and technical roadmap aligned with your goals and budget.
- 03
Development & implementation
We build the solution with engineering best practices and constant communication.
- 04
Testing & deployment
We validate quality, performance and security before a controlled production rollout.
- 05
Support & continuous improvement
We support operations with monitoring and evolutionary improvements to the solution.
Related case studies
Reputation bomber detection on social networks
Challenge: Coordinated campaigns on TikTok, Facebook and Instagram were attacking corporate reputation without a timely way to identify the actors or sabotage patterns.
Solution: AI and data analysis platform on Neo4j, with a RAG that correlates accounts, content and behavior across social networks to detect reputation bombers and provide evidence on alleged corporate sabotage groups.
- Neo4j
- Python
- NLP
- RAG
- Cloud
Cloud platform for information processing
Challenge: Large volumes of business information had to be received, validated, processed and stored reliably and at scale.
Solution: Event-driven architecture on AWS, with asynchronous processing, automatic validation and structured storage.
- AWS
- API Gateway
- S3
- DynamoDB
- Lambda
- SNS
- CloudWatch
Frequently asked questions
What is RAG and why is it useful for a company?
RAG (retrieval-augmented generation) combines a language model with a search over your own documents. The model answers using the retrieved information and can cite the source, which reduces made-up answers and lets you use up-to-date internal knowledge without retraining the model.
Is my data safe if I use generative AI?
We design the solution around the confidentiality level of your data: we choose providers and settings that don't use your information to train their models, apply per-user access control and, when required, deploy models in your own cloud.
How much does it cost to implement AI in my company?
We recommend starting with a focused proof of concept on a specific use case, which lets you measure real results with a controlled investment. Running costs depend mainly on model usage volume, and we estimate them from the start.
Can you integrate AI with our ERP or CRM?
Yes. We connect models through APIs and databases so the AI can look up information, record results or trigger processes in your systems, respecting each user's permissions.
Will AI replace my team?
In practice, AI works best as support: it automates repetitive tasks and delivers information faster, while decisions and validation stay with people. We design workflows where your team supervises and improves the results.
Shall we talk about your project?
Tell us what you need and we'll propose a solution with clear scope, timeline and budget.