Assistant embedded in the interface
An assistant that answers the user’s questions based on their account data, the documentation or the history, and that can trigger authorized actions.
AI in your products
AI Features for Your Product: Capabilities Your Customers Find Useful
Integrating AI into your product means adding features your customers actually use: an assistant in the interface, a search that understands questions, automatic extraction or summarization of documents. We design, develop and run them as full-fledged components of your software.
For
Software vendors and SaaS platforms whose customers expect useful AI features
What you get
Assistant, natural-language search, extraction or summarization, built into your code and tested
Deliverables
Code and tests, evaluation set, usage tracking, technical and operations documentation
Format
A first feature as a fixed-price project, then a dedicated team to keep evolving the product
What we build
AI features built into your product, not bolted on.
For a software vendor or a SaaS platform, AI only has value if it fits into existing user journeys: in the right place in the interface, with the customer’s data, respecting their permissions and at a cost compatible with your business model.
We take charge of the AI service, its integration into the screens, usage tracking and the rules specific to each customer. The model becomes a software component, with a controlled interface, tests and release cycle.
Natural-language search and questions
A search that understands the user’s intent across your content, records or documents, with sources displayed.
Document extraction and processing
Reading invoices, contracts, forms or meeting notes, extracting the relevant fields and checking them before they are saved in your product.
Summarization, drafting and classification
Case file summaries, draft replies, automatic categorization: concrete time savings, with user validation when needed.
Who it is for
When should you add AI to your software?
Your customers are asking for AI
Competitors are announcing AI features and your customers are asking you about them. You need to choose the use cases that bring real value rather than a gimmick.
A repetitive task is slowing your users down
Document entry, information search, drafting replies: a well-placed AI feature can remove a step from the user journey.
Your product team is busy with the roadmap
We build the AI features in parallel, in your code and following your practices, without slowing down other development.
From work to deliverables
From feature idea to production.
Choose the use case and measure its value
We start from your users’ journeys and define what the feature must produce, from which data, and how to measure that it is useful.
Prototype on your data
Comparison of models and approaches on real examples, with an initial estimate of the running cost per user or per customer.
Develop and integrate
AI service, API, interface, multi-tenant management, access rights, logs and tests. The feature is delivered like the rest of your product.
Run and evolve
Tracking of quality, errors and usage, gradual rollout per customer, improvements based on feedback.
What your team receives
- Code integrated into your product, with tests
- Evaluation dataset and usage tracking dashboard
- Technical and operations documentation
The choices that matter
Quality, confidentiality and cost per customer.
Three questions shape an AI feature in a product: is the quality of the answers measured and tracked? Does each customer’s data stay isolated and processed according to your commitments? Is the usage cost compatible with your pricing?
We compare OpenAI, Claude and Gemini models on your use cases, and integrate AI into your existing stack — for example a Symfony or Node.js application. For agents that can act within your tools, see AI agents and chatbots.
The collaboration framework
Getting started with a first use case.
Tell us about your product, your users and the AI use case you have in mind. We can deliver a first feature as a fixed-price project, then continue with a dedicated team that evolves your product and its AI features. Already have a prototype? See AI POC takeover.
Frequently asked questions
AI in your product: your questions.
Which AI features should you add to a SaaS product?
The most useful are often an embedded assistant that answers based on the customer’s data, natural-language search, automatic document extraction and summarization or assisted drafting. The right choice depends on the tasks that take your users the most time.
Do we need to rewrite our software to integrate AI?
No. AI features are integrated as services of your existing application, in your language and framework, with the same security, testing and deployment rules as the rest of the code.
How do you protect our customers’ data?
By isolating data per customer, applying the user’s permissions to every request, choosing models and hosting terms compatible with your commitments, and logging access. See also our precautions for AI in the enterprise.
How much does an AI feature cost to run?
The cost depends on the model, the volume of requests and the size of the content processed. We measure it from the prototype stage, per user or per customer, and optimize it by choosing the right model for each step and limiting the context sent.
How do you know if the AI feature is good quality?
With a set of reference examples and evaluations rerun at every change, complemented by production tracking of user feedback and errors.
Can you work with our product team?
Yes. We work in your code, your tools and your rituals, in coordination with your product team, or we take charge of a feature end to end.
Which AI feature for your product?
Tell us about your software, your users and the use case you have in mind. We will help you choose the first use case to build and estimate its running cost.