AI Development for systems that solve real business problems
We design and build custom AI applications, retrieval systems, recommendation engines, search experiences, classifiers, and copilots tailored to your workflows, data, and users. From prototype to production, we focus on usefulness, integration, and measurable performance.
Solutions
Off-the-shelf tools are useful, but many companies need AI systems shaped around their own products, taxonomy, content, operations, and customer journey. Inferendo develops custom solutions for teams that need more than a generic plugin or isolated experiment.
Our experience in recommendation and search-led commerce provides a strong foundation for broader AI development, especially where relevance, matching, ranking, classification, and contextual retrieval matter. Public descriptions of Inferendo and Visidea already point to these strengths in visual search, semantic search, and personalized recommendations.
What we build
- Custom models and AI applications — Tailored systems built around your use case, data structure, and business logic.
- Recommendation systems — Product, content, or action recommendations based on behavior, similarity, context, or rules.
- Search systems — Visual search, semantic search, hybrid retrieval, ranking, and result optimization.
- Classification systems — Tagging, categorization, routing, moderation, and structured labeling workflows.
- Semantic retrieval — Knowledge access, document retrieval, vector search, and contextual answer systems.
- AI copilots — Internal assistants for support, operations, sales, catalog management, or knowledge-heavy workflows.
Delivery approach
- Problem definition
We align on the user problem, operational context, target outcomes, and performance criteria. - Data and architecture design
We define the data flows, retrieval logic, model strategy, integration points, and evaluation method. - Prototyping
We build a focused prototype to validate quality, relevance, latency, and usability before scaling. - Production delivery
We implement the system in a stable architecture, connected to the necessary tools and workflows. - Iteration and optimization
We monitor outputs, refine models and prompts, improve ranking or retrieval quality, and align the system with business KPIs.
Example development projects
- A recommendation engine for a retail catalog.
- A semantic search layer for products or internal knowledge.
- A visual search experience for e-commerce product discovery.
- An AI classifier for ticket routing or document categorization.
- A copilot for sales teams, support teams, or internal operations.
- A retrieval-based assistant connected to company documentation.
Why Inferendo
Inferendo combines product thinking with implementation capability. The company’s visible work in recommendation systems, visual search, and AI-powered commerce shows experience in building systems where relevance and user experience directly affect outcomes such as discovery, engagement, and conversion.
We build AI that fits the business it serves. Whether the goal is better discovery, faster decisions, more automation, or a new product capability, development starts from a clear operational need and ends with a usable system.