We’re Liive
From idea to live product
Independent AI & Data Product Studio
A founder-led studio for AI products, data-rich apps and workflow systems.
From first concept to shipped software.
I’m Mohamed Redjimi, a software engineer based in France. Through Liive, I build AI and data-driven products where product thinking, engineering and user experience need to work as one.
Before Liive, I worked across environments with very different constraints: small teams, venture-backed fintech, technical research, industrial manufacturing and global telecom. That range matters because client projects rarely fail from code alone; they fail when speed, data complexity, user experience and operational reliability are not handled together.
01 Product engineeringFrom rough idea to shipped system
02 AI workflowsAgents, tools, routing, memory
03 Data-rich appsRecommendations, analytics, pipelines
04 Mobile + fullstackApps, APIs, Firebase, payments
LexPrivé
Private-client legal workflows, research support and AI operator thinking.
Legal AI · agents · workflow systems
Liive City
A modular local-services product spanning mobility, commerce, events and everyday city life.
Mobile product · backend · marketplace
Marriage AI
Compatibility, profile quality and matching pipelines for a product where trust matters.
Matching logic · data pipelines · Firebase
Ride Sharing
A standalone native app concept using existing backend pieces and real trip-planning logic.
Native app · Firebase · trip planning
Personal Operator
An AI operator for follow-through: context, tasks, reminders, tools and human handoff.
Agents · memory · tool use
Mosque App
Community, prayer, learning and local operations shaped into a practical app direction.
Community product · mobile · content
More projects I worked on[ selected above ]
A compact index of other projects, from AI operators to data-rich apps and local products.
Each project has its own context, roadmap and operating thread, so the ideas do not collapse into one vague “AI platform”. Some are product bets, some are internal operators, and some are focused experiments around a specific market.
The common thread is simple: build enough of each project to learn from reality, then make the useful parts stronger.
Smarter ordering flows for restaurants and service businesses.
Careful AI assistance around health workflows.
Structured verification work for Islamic references.
Back-office intelligence for small businesses.
Coaching systems for training, recovery and consistency.
A local gym product grounded in a real place.
Market watching, signals and disciplined decision support.
Short-form explainers for making complicated topics clearer.
Recruiting workflows, matching and candidate operations.
Practice environments for better human conversations.
Software thinking around care, coordination and support.
AI usage with a sharper eye on cost and footprint.
Commerce experiments from storefront to operations.
Events, access and lightweight ticketing flows.
Tools for small operators who need practical software.
Business visibility, margins and decisions in one place.
Trip recommendation work for self-driving vehicle scenarios.
Structured retrieval and indexing for Islamic Q&A material.
A focused company thread for building and testing quickly.
Sports, movement and local community product work.
What I learned building operators as real product work.
The useful work is rarely the model call. It is the routing, context, permissions, retries and human handoff around it.
EssayThu 19 Nov
The product work between an AI demo and something people trust.
ProcessWed 8 Apr
Why I keep many small projects around one bigger idea.
TalkWed 18 Mar