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About Contact Us
AI-first engineering

AI Product Development Services.

Logiciel provides AI product development services for companies building intelligent applications, adding AI to existing products and automating complex workflows. From use-case discovery and data readiness to AI application development, model integration, evaluation, cloud engineering and managed operations, we help teams move confidently from experimentation to measurable product outcomes.

Get started

See Logiciel in action.

Tell us what you're building and we'll take it from there.

5 steps
Stages in the AI product development framework
3 models
Engagement models for AI product delivery
Why Logiciel

Why AI Product Development Services Matter.

Why Logiciel · 01

AI features may fail when they encounter incomplete data, unusual requests or changing business rules.

Why Logiciel · 02

Different user roles and permission levels can create complex data-access and security requirements.

Why Logiciel · 03

Unclear use cases can lead to technically impressive products that do not improve a measurable business outcome.

Why Logiciel · 04

Unreliable source data can reduce the accuracy, relevance and consistency of AI-generated outputs.

Why Logiciel · 05

AI pilots often remain disconnected from the applications and workflows where users need them.

Why Logiciel · 06

Model latency, operating costs and unpredictable behaviour can affect adoption and product economics.

Why Logiciel · 07

Companies need a coordinated model combining product strategy, data engineering, software development, evaluation, security and monitoring.

What you get

What You Get When You Work With Logiciel on AI Product Development.

Each engagement is designed to create an AI product your internal team can understand, operate and continuously improve.

01

An AI product roadmap

aligned with business priorities and measurable user outcomes

02

Clearly defined use cases

quality thresholds and success criteria

03

Senior product

AI, data, software and cloud engineers matched to your environment

04

Scalable application architecture

data pipelines and retrieval workflows

05

Secure integration

with approved business systems, applications and data sources

06

Evaluation frameworks

automated testing and human-review controls where required

07

Monitoring

cost visibility, documentation and an operating model your team can maintain

What we build

AI Product Development Solutions.

01

AI Product Strategy and Discovery

User research, workflow analysis, feasibility assessment, product definition and measurable success criteria for valuable AI opportunities.

02

Generative AI Application Development

Applications that generate approved content, summaries, reports, recommendations and responses within defined product and business rules.

03

AI Assistants and Intelligent Search

Assistants, copilots, semantic search and knowledge-retrieval experiences that help users find information and complete defined tasks.

04

Document AI and Workflow Automation

Document extraction, classification, comparison, validation, summarization and integration with operational workflows.

05

Retrieval and Data Engineering

Data pipelines, transformations, knowledge systems and retrieval-augmented generation connecting AI products with approved information.

06

Agentic AI and Decision Support

Controlled agents, recommendations, natural-language analytics and next-best-action capabilities with permissions and approval controls.

07

AI Evaluation and Managed Operations

Quality evaluation, security, monitoring, cost optimization, incident response and continuous product and model improvement.

Engagement

Engagement Models Designed for AI Product Delivery.

01

AI Product Discovery and Validation

A focused engagement identifying the right use case, assessing data readiness and producing a testable product concept with measurable outcomes.

Engagement
02

Dedicated AI Product Engineering Squad

A cross-functional team working continuously across product, application, data, AI, testing, integration and cloud workstreams.

Engagement
03

Outcome-Based AI Product Development

A defined engagement organized around agreed milestones and measurable outcomes for a new product, AI feature or production-readiness initiative.

Engagement
Under the hood

AI Product Development Services We Deliver.

01

AI Product Diagnostic and Roadmap

What it meansAssessment of the user problem, workflow, data, technical environment, product opportunity and expected business value.
02

Generative AI Applications and Assistants

What it meansProduction-ready applications, assistants and copilots supporting intelligent search, content preparation, summarization and workflow guidance.
03

Retrieval, Knowledge and Document Engineering

What it meansRetrieval systems, semantic search, document extraction, classification, comparison, validation and knowledge-grounded experiences.
04

AI Workflow and Agentic Automation

What it meansIntegration of AI with approved APIs and business systems to support defined multi-step tasks with appropriate controls.
05

Data Engineering and AI Integration

What it meansPipelines, transformations, model integration, application APIs and connections with existing products and internal platforms.
06

AI Evaluation, Security and Quality Engineering

What it meansEvaluation datasets, regression tests, permissions, data boundaries, auditability, safeguards and failure-handling processes.
07

Managed AI Product Operations

What it meansOngoing feature delivery, production monitoring, model evaluation, incident response, cost optimization and continuous improvement.
Insights

AI Product Development Insights & Frameworks.

01

Patterns from our product, AI, data and software engineering teams that help companies move from promising experiments to reliable production applications.

↳ Insights
02

AI Product Value and Readiness Model

How we evaluate user value, workflow fit, data quality, technical feasibility, operating cost and implementation risk before product development begins.

↳ Insights
03

Production AI Quality Framework

A practical approach to measuring accuracy, relevance, consistency, latency, safety, cost and failure handling across representative scenarios.

↳ Insights
How we work

Our AI Product Development Framework.

01

Opportunity and Success Definition

We assess the user problem, business workflow and product opportunity and define measurable outcomes such as accuracy, adoption, completion rate or reduced manual effort.

02

Data and Knowledge Readiness

We evaluate the quality, ownership, permissions and accessibility of required data and build retrieval systems or pipelines where needed.

03

Product, Architecture and Workflow Engineering

We design the user experience, application architecture, integrations, models, APIs and review paths and build them through visible sprint cycles.

04

Evaluation, Security and Production Hardening

We test AI behaviour across users, prompts, data conditions and failures while strengthening access controls, monitoring, safeguards and cost visibility.

05

Controlled Launch and AI Operating Model

We introduce capabilities through pilot users or phased releases and provide evaluation practices, documentation and runbooks for continuous improvement.

Questions

Frequently asked questions.

What do AI product development services include?

AI product development services can include use-case discovery, data engineering, application development, model integration, retrieval systems, evaluation, security, cloud infrastructure and managed operations.

What is AI product development?

AI product development is the process of designing, building, testing, launching and continuously improving software products that use AI to deliver a defined user or business outcome.

How is AI application development different from a prototype?

A prototype demonstrates whether an idea may work. A production AI application also requires reliable data, user permissions, evaluation, security, monitoring, integrations and failure-handling processes.

Can Logiciel add AI to an existing product?

Yes. Logiciel can assess existing applications, data and workflows and introduce capabilities such as intelligent search, assistants, document processing and workflow automation.

Does every product need AI?

No. AI should be used where interpretation, generation, prediction or assistance creates clear value. Predictable workflows are often better handled through conventional software.

How does Logiciel evaluate AI product quality?

Logiciel defines representative test cases and quality criteria for accuracy, relevance, consistency, latency, cost and failure handling.

Who owns the AI product and source code?

Your organization retains ownership of the source code, application architecture, data pipelines, automated tests, documentation and other agreed deliverables.

Does Logiciel provide support after launch?

Yes. Ongoing support can include feature delivery, production monitoring, AI evaluation, model updates, incident response, cost optimization and continuous product improvement.

Let's build

Turn Your AI Opportunity into a Production-Ready Product.

Move beyond disconnected experiments with a senior AI product engineering team that can take your idea from discovery through production.