LLM integrations, AI feature development, and end-to-end AI SaaS platforms built for production scale.
LLM integrations, AI feature development, and end-to-end AI SaaS platforms built for production scale.
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.
From LLM integration to custom ML models built on your data.
OpenAI, Anthropic, and open-source LLMs (Llama, Mistral) — integrated into your product workflows.
Retrieval-augmented generation — ground LLM responses in your product data for accuracy.
Automate repetitive user workflows with AI — document extraction, classification, and summarisation.
Train models on your data for predictions, anomaly detection, and classification specific to your domain.
Automated evaluation of LLM outputs against ground truth — know when your AI is working and when it is not.
Domain-specific fine-tuning and embedding models for search, recommendations, and semantic matching.
Scoped during Discovery Sprint — your system includes only what your operation needs.
Extract structured data from PDFs, invoices, contracts, and forms — with high accuracy on domain-specific documents.
In-product AI assistant grounded in your data answers user questions, drafts content, and suggests actions.
Vector-based search that understands intent, not just keywords — across your product content and customer data.
Classify support tickets, leads, transactions, or documents automatically with ML models trained on your data.
Churn prediction, lead scoring, demand forecasting ML models trained on your product data.
AI-powered content drafting, summarisation, and personalisation integrated into your product UI.
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.
Understand your product vision, target users, and SaaS business model (pricing, onboarding, growth).
Design multi-tenant architecture, billing systems, data models, and scalable infrastructure.
Build core features in fast iterations with working demos every two weeks.
Set up CI/CD, cloud environments, monitoring, and production-grade deployment pipelines.
Launch your SaaS with confidence — onboarding, analytics, and performance tracking in place.
Iterate based on real user data optimize retention, pricing, and feature adoption.
From AI features to production-ready systems — start with a Discovery Sprint
Svvatech
Production-grade software for manufacturing, logistics, and SaaS startups. Built in Chennai, deployed globally.
© 2025 Svavvashaa Technologies Pvt Ltd.
All rights reserved.
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Production-grade software for logistics,manufacturing,and SaaS startups. Built in Bengaluru, deployed globally.
© 2026 SVVATECH Pvt Ltd.
All rights reserved.
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