AI-Powered SaaS Products
LLM integrations, AI feature development, and end-to-end AI SaaS platforms built for production scale.
AI - Powered SaaS Products
LLM integrations, AI feature development, and end-to-end AI SaaS platforms built for production scale.
Most "AI Features" Are Demos That Do Not Survive Real Users.
Adding an AI wrapper to a SaaS product is easy. Building AI features that reliably work on real user data, integrate into actual workflows, and improve measurable product metrics — that is hard.
Production AI features require the right model choice, a grounding strategy, evaluation pipelines, and careful UX integration — so they work reliably, not just in demos.
AI Product Capabilities
From LLM integration to custom ML models built on your data.
LLM Integration
OpenAI, Anthropic, and open-source LLMs (Llama, Mistral) — integrated into your product workflows.
RAG Pipelines
Retrieval-augmented generation — ground LLM responses in your product data for accuracy.
AI Workflow Automation
Automate repetitive user workflows with AI — document extraction, classification, and summarisation.
Custom ML Models
Train models on your data for predictions, anomaly detection, and classification specific to your domain.
AI Evaluation Pipelines
Automated evaluation of LLM outputs against ground truth — know when your AI is working and when it is not.
Fine-Tuning & Embeddings
Domain-specific fine-tuning and embedding models for search, recommendations, and semantic matching.
AI Features We Build Into Your Product
Scoped during Discovery Sprint — your system includes only what your operation needs.
Document Intelligence
Extract structured data from PDFs, invoices, contracts, and forms — with high accuracy on domain-specific documents.
AI Chat & Copilot
In-product AI assistant grounded in your data answers user questions, drafts content, and suggests actions.
Semantic Search
Vector-based search that understands intent, not just keywords — across your product content and customer data.
Automated Classification
Classify support tickets, leads, transactions, or documents automatically with ML models trained on your data.
Predictive Analytics
Churn prediction, lead scoring, demand forecasting ML models trained on your product data.
Content Generation
AI-powered content drafting, summarisation, and personalisation integrated into your product UI.
Common Questions
We select the right model based on your use case, accuracy needs, cost, and data residency requirements.
We use retrieval-augmented generation (RAG) to ground responses in your data, combined with evaluation and monitoring systems to detect and reduce hallucinations in production.
Yes. We fine-tune or train models on your proprietary data for classification, prediction, and domain-specific use cases delivering higher accuracy than generic LLMs.
A focused AI feature (e.g., document extraction or semantic search) typically takes 6–10 weeks. Full AI integrations or copilots usually take 12–16 weeks, depending on scope.
Yes. We design AI features to integrate seamlessly with your existing workflows, APIs, and data systems, so they enhance your product without disrupting it.
How We Build AI into Your Product
Discovery Sprint
Understand your product vision, target users, and SaaS business model (pricing, onboarding, growth).
Architecture
Design multi-tenant architecture, billing systems, data models, and scalable infrastructure.
MVP Build Sprints
Build core features in fast iterations with working demos every two weeks.
Launch-Ready Infrastructure
Set up CI/CD, cloud environments, monitoring, and production-grade deployment pipelines.
Go Live & Scale
Launch your SaaS with confidence — onboarding, analytics, and performance tracking in place.
Continuous Growth
Iterate based on real user data optimize retention, pricing, and feature adoption.
Ready to Add AI to Your Product?
From AI features to production-ready systems — start with a Discovery Sprint