From strategy through engineering to scale — every capability modern enterprises need to operationalise AI.
Enterprise AI transformation needs engineering muscle, domain knowledge, and a model built for production — not advisory decks.
Every initiative anchored in cost reduction, revenue growth, or efficiency. We never build AI for its own sake — every line of code connects to a business result.
Idea to production in under 12 weeks. No long consulting engagements. The FDE model eliminates the handoff gap that kills most enterprise AI initiatives.
FDE engineers work inside your organisation — in your codebase, your sprints, your systems. They build AI that fits your reality, not a generic template.
Data isolation, RBAC, audit logging, and responsible AI governance built in from day one — not bolted on after the fact. We design all AI with compliance at the core.
We define measurable success criteria before we start and report against them throughout. Results are our responsibility — not just yours.
Pattern recognition from real deployments across 10+ industries. Banking, Healthcare, Manufacturing, Retail, Insurance — we understand your world before we build in it.
We bring pattern recognition from real deployments across every major vertical. We understand your world before we build in it.
Credit risk AI · Fraud detection · Regulatory automation · Wealth copilots · Intelligent onboarding
Predictive maintenance · Quality inspection AI · Supply chain intelligence · Production optimisation
Clinical documentation AI · Patient flow · Medical imaging analysis · Prior authorisation automation
Personalisation engines · Demand forecasting · Conversational commerce · Dynamic pricing AI
Network operations AI · Churn prediction · AI customer care · Revenue assurance automation
Claims automation · AI underwriting support · Fraud intelligence · Customer service AI
Intelligent document processing · AI-augmented F&A · Agentic back-office automation
AI product features · LLM integration · AI-native architecture · Growth AI at startup pace
AI maturity assessment, stakeholder interviews, data landscape review, and use case prioritisation across your enterprise.
Technical architecture, technology selection, security framework, team structure, and a sprint-by-sprint 12-week build plan.
FDE engineers embedded and shipping — AI features, agents, and infrastructure built, tested, and deployed into your production environment.
Performance monitoring, model optimisation, new use cases, and structured knowledge transfer to your internal team.
Real AI deployments. Real business challenges. Measurable outcomes — achieved through embedded engineering.
Our FDE engineers embed directly inside your organisation — working in your codebase, your Jira, your sprint ceremonies — as a fully integrated part of your AI team.
Written from experience, not theory. Practical insights from real deployments and production AI systems.
An analysis of the root causes of AI pilot failure in large enterprises, and how Forward Deployed Engineering addresses each one systematically.
Read articleA behind-the-scenes look at how Innovsol structures its 12-week FDE engagement — week by week, from discovery through to go-live.
Read articleA practical framework for choosing between Retrieval-Augmented Generation and fine-tuning for enterprise LLM applications.
Read articleWe are looking for engineers, scientists, and builders who want to move fast, work on hard problems, and see their work running in production at scale.
Join enterprises that have made AI operational. Our FDE engineers are ready to embed with your team and build AI that works in the real world — not just in demos.
Join the FDE team. Embed in ambitious enterprises. Work on hard problems. See your AI running in production — fast.
Whether you're exploring AI for the first time or ready to scale — a conversation with our team is the fastest way forward.
Tell us about your AI challenge — our team will respond within 1 business day.