From Generative AI Pilot to Production
Most generative AI projects stall at the demo. Stellen Infotech is a generative AI development company that takes you the rest of the way — from identifying the use cases with real ROI, to building secure LLM applications on OpenAI, Anthropic Claude, Google Gemini or open-source models, to integrating them into the software your teams use every day.
With 15+ years of custom software development and our own AI-enabled SaaS products in production, we bring engineering discipline to GenAI: proper data pipelines, evaluation, cost control and governance — not just prompts.
Our Generative AI Development Services
Generative AI Consulting & Strategy
Use-case discovery, feasibility assessment, build-vs-buy analysis, data readiness and a prioritised roadmap with expected ROI for each initiative.
Custom LLM Application Development
Web and mobile applications built around large language models — document generators, contract analysers, content engines, coding assistants and domain-specific copilots.
RAG & Enterprise Knowledge Systems
Retrieval-augmented generation over your documents, databases and tickets — with vector search, access control and citations — so answers are accurate and traceable.
LLM Fine-Tuning & Model Selection
Benchmarking GPT, Claude, Gemini, Llama and Mistral for your task; fine-tuning or distilling smaller models to cut cost and latency while keeping quality.
AI Copilots for Existing Software
Embedding generative AI into your CRM, ERP, SaaS product or internal tools — natural-language search, auto-summaries, smart forms and recommendations.
Image, Voice & Multimodal AI
Product-image generation, visual search, speech-to-text, text-to-speech and document OCR pipelines combined with LLM reasoning.
Generative AI Use Cases We Have Delivered
- Real estate — listing descriptions, buyer-matching and Arabic/English property assistants
- Salons & wellness — AI booking assistants and marketing content inside Salonist
- E-commerce — product copy at scale, visual search, personalised recommendations
- Healthcare — patient-intake summarisation and clinical documentation drafts
- Legal & professional services — contract review, clause extraction, proposal generation
- Customer support — reply drafting, ticket summarisation and knowledge-base chat
- Marketing agencies — SEO content pipelines, ad-copy variants and reporting narratives
- Finance & operations — invoice extraction, report generation and anomaly explanations
Our Generative AI Development Process
- Discovery workshop — map processes, data sources and pain points; shortlist 2–3 use cases by value and feasibility.
- Data & model assessment — audit data quality and privacy constraints; benchmark models on your samples.
- Proof of concept (2–4 weeks) — a working prototype measured against agreed accuracy and cost targets.
- Production build — scalable architecture, integrations, evaluation suites, guardrails and monitoring.
- Rollout & change management — training for your team, phased launch and feedback loops.
- Continuous improvement — quality monitoring, cost optimisation and model upgrades as the landscape moves.
Why Stellen Infotech for Generative AI
- We ship products, not decks. Our own SaaS platforms run GenAI features for thousands of businesses.
- Full-stack delivery. AI engineers plus Laravel, Node.js, React and mobile teams under one roof — no hand-offs between vendors.
- Cost discipline. Model routing, caching and right-sizing keep your monthly LLM bill predictable.
- Responsible AI. Bias checks, human-in-the-loop design, PII protection and audit trails as standard.
- Regional expertise. Arabic-first solutions for the GCC, data-residency options for UAE and India.
- Offices in India, Dubai and the USA — 15+ years, 5,000+ projects delivered.
Frequently Asked Questions
What is generative AI development?
Building software that uses models like GPT, Claude or Gemini to create text, images, code or decisions — and wiring that capability into real business workflows with the right data, security and controls.
Do we need our own data to benefit?
You already have it — documents, emails, tickets, product data. RAG lets models use that data without expensive training. Fine-tuning is only needed for highly specialised tasks, and we tell you when it is not worth it.
How much does a generative AI project cost?
A proof of concept typically runs 2–4 weeks at a fixed price. Production systems are scoped after the PoC once accuracy and cost are proven. We also offer generative AI consulting as a standalone engagement.
Which model should we use?
It depends on the task, language, budget and data-residency needs. We benchmark several models on your own samples and recommend the best fit — often a mix, with cheaper models handling routine work.
How do you keep our data secure?
Enterprise API agreements with zero data retention, private cloud or on-premise deployment, encryption in transit and at rest, and role-based access to every knowledge source.
Start With a Free Generative AI Opportunity Assessment
A 45-minute session with our AI team to identify the highest-value use case in your business and what it would take to build.
