FieldFlow AI by Ginqel turns intervention requests into planned operations: AI-assisted qualification, skill matching, workflow automation and field scheduling optimization.
Personal project in development: a platform prototype built for maintenance, after-sales service, facility management and mobile operations teams.
FieldFlow AI by Ginqel brings together information, automation and field operations in an experience designed to simplify the work of managers and technicians.
FieldFlow AI by Ginqel helps structure the information useful to the intervention: type of need, urgency, location, constraints and skills required.
The intervention's needs can be matched against skills, availability and coverage areas to help the manager with assignment.
Managers get a centralized view of interventions and resources to prepare and adjust field organization.
Intervention information is brought together to make it easier to track between operational teams and field workers.
The manager organizes operations from the web interface. The technician finds on mobile the information needed to carry out their interventions.
Interventions, customer information, location and operational tracking, accessible from an interface designed for the field.
Browse the prototype’s screens: qualification, scheduling, field tracking and the mobile app.
Operational teams often already have the information they need, but it's spread across several tools and still requires many manual actions.
FieldFlow AI by Ginqel aims to connect requests, data, resources and scheduling to simplify the teams' work and speed up operational decisions.
Multi-channel intake (web, phone, email, API)
Needs analysis with an LLM (NLP)
Skills, location, availability, SLA
Intelligent assignment algorithm
Automatic proposal to the technician
Updates and re-optimization as needed
Skills, availability, location, urgency and workload can all be factored in to propose a more coherent organization of interventions.
FieldFlow AI by Ginqel combines artificial intelligence, automation, IT system integration and operational management in one unified experience.
An architecture designed to apply artificial intelligence to concrete operational challenges.
Reduce manual tasks and simplify the day-to-day organization of field interventions.
An approach that fits organizations managing mobile resources and interventions.
An API-driven design with access control and secure-exchange mechanisms.
Explore the features, architecture, use cases and resources to understand how FieldFlow AI by Ginqel can fit into field operations.
Discover how FieldFlow AI by Ginqel qualifies requests, selects resources and organizes interventions.
Explore the featuresExplore the target architecture combining artificial intelligence, automation, APIs and operational data.
Discover the technologyMaintenance, after-sales service, facility management, telecommunications, industry and mobile teams.
See the use casesGuides, use cases and content about AI, automation and field operations.
See the resourcesFieldFlow AI by Ginqel is designed and built in France, as a personal project, by an engineer who knows critical systems and AI.
Design and development · Java and AI Tech Lead
Software engineer for 10 years, including 8 years of Java / Spring Boot on critical systems (banking, insurance, pensions, public sector), and Tech Lead since 2021. He builds FieldFlow AI by Ginqel to explore AI applied to field operations.
The essentials to understand the project, its progress and its technical choices.
FieldFlow AI by Ginqel is a personal project by Yacine Amouche. It explores backend architecture, automation and artificial intelligence applied to field operations: maintenance, after-sales service, technical services and multi-site interventions.
No. FieldFlow AI by Ginqel is a personal prototype in development: it is neither sold nor offered for trial. The screens shown on this site illustrate the project’s direction and progress.
Organisations already rely on ERP, CRM and business applications. The project is therefore designed as a layer that connects to existing systems through APIs, rather than a tool that would replace everything.
No. In FieldFlow AI by Ginqel, AI helps qualify requests and suggest assignments; business rules and human validation remain at the heart of the process.
A Java / Spring Boot backend with PostgreSQL, a Flutter mobile app and containerised deployment with Docker. Request qualification combines business rules with an optional language model.
Yes, gladly: technical questions, feedback on the architecture or professional exchanges. FieldFlow AI by Ginqel remains a personal project: no services or commercial offer are provided.
FieldFlow AI by Ginqel grew out of a wish to explore, on a concrete case, backend architecture, automation and artificial intelligence applied to field operations. The project moves forward in stages, shared here as development progresses.
