Paris AI Engineering Studio

AI Engineering for scalable business products

Binov helps companies design, build, and industrialize AI-powered products from strategy to scalable engineering delivery.

We work with ambitious teams that want to move beyond AI experiments and ship real products: copilots, RAG applications, AI agents, workflow automation, and intelligent SaaS features.

From strategy to production delivery
Senior product + AI engineering leadership
Built for adoption, observability, and governance

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Most AI initiatives do not fail because of the model. They fail because they never become products.

Many AI initiatives remain stuck at the prototype stage: impressive demos, weak system integration, uncontrolled LLM costs, limited security, poor user experience, no observability, and no clear path to production.

Binov helps companies turn AI opportunities, prototypes, and business needs into robust, maintainable, and scalable products.

What we build

AI copilots
Business assistants connected to documents, internal tools, CRM, ERP, and knowledge bases.
RAG applications
Semantic search, document assistants, chat with your data, source citations, and controlled knowledge retrieval.
AI agents
Agents that orchestrate business tasks such as qualification, support, analysis, reporting, and workflow automation.
AI-powered SaaS features
AI features integrated into existing products: summarization, extraction, classification, recommendations, and content generation.
Workflow automation
AI-powered automation using APIs, internal systems, n8n-style workflows, and business tools.
AI product MVPs
Fast development of AI MVPs with clean architecture and a clear path to scalability.

From AI prototype to production-grade product

AI prototype

Manually tested prompts
Isolated demo
No cost control
Untraceable answers
Basic UX
Limited security

Production-grade AI product

Versioned and observable AI chains
Real system integration
Token, latency, and usage monitoring
Sources, logs, feedback, and auditability
UX designed for adoption
Authentication, permissions, governance, and data isolation

Engineering capabilities

Product & UX engineering
We design AI experiences for real users: chat interfaces, copilots, workflows, dashboards, and business applications.
LLM integration
We integrate OpenAI, Azure OpenAI, Mistral AI, Anthropic, or private models depending on business, security, and deployment constraints.
RAG & knowledge systems
We build document ingestion pipelines, chunking strategies, embeddings, hybrid search, citations, permissions, and source synchronization.
Cloud & backend architecture
We design APIs, workers, queues, event-driven systems, scalable backends, monitoring, and secure cloud architecture.
Evaluation & observability
We monitor answer quality, user feedback, token costs, latency, hallucinations, and regression risks.
Security & governance
We implement access control, confidentiality, auditability, data isolation, and enterprise-grade governance.

AI use cases we can deliver

Internal document assistant
Reduce search time and make internal knowledge easier to access.
Customer support copilot
Accelerate answers, standardize quality, and reduce support workload.
Document analysis automation
Extract, classify, summarize, and compare PDFs, contracts, invoices, and reports.
Sales qualification agent
Prepare leads, enrich data, generate summaries, and support sales teams.
Business copilot connected to internal systems
Let teams interact with operational data through a natural language interface.
Personalized recommendations
Recommend products, actions, or offers based on context, history, and business rules.
Controlled content generation
Generate emails, reports, product descriptions, or summaries with guardrails.

Our delivery approach

Step 1
Discover
Clarify the business need, use cases, constraints, risks, available data, and success metrics.
Step 2
Design
Define the user journey, target architecture, model strategy, data strategy, and KPIs.
Step 3
Build
Develop the product, AI workflows, APIs, interfaces, integrations, and security foundations.
Step 4
Evaluate
Test answer quality, cost, latency, robustness, UX, and business relevance.
Step 5
Scale
Industrialize the solution with monitoring, documentation, continuous improvement, and handover.

Why Binov

Binov combines product thinking, AI engineering, and scalable delivery capacity. We do not only advise on AI opportunities. We help companies ship production-ready products.

Paris-based AI engineering studio serving France & Europe
Product, tech, cloud, and AI expertise
Scalable engineering delivery capacity with nearshore execution support from Tunisia
Pragmatic delivery culture
From strategy to implementation
Built for real business adoption

Explore related pages

Discover how Binov supports execution with a practical delivery model and complementary services.

Indicative technology stack

Our stack choices are driven by product constraints, team maturity, security requirements, and long-term maintainability.

Frontend
Next.js, React, TypeScript, Tailwind CSS
Backend & APIs
Node.js, NestJS, Python, FastAPI
AI & LLM
OpenAI, Azure OpenAI, Mistral AI, LangChain, Vercel AI SDK
Search & data
Azure AI Search, PostgreSQL, pgvector, embeddings, document intelligence
Cloud & DevOps
Azure, GCP, Docker, CI/CD, observability

Companies We've Worked With