OpenAI · Claude · LLM APIs
You don't need a new product to use AI. We add features like summaries, smart search, drafting and classification to the software you already have, with limits on cost and checks on quality.
In Short
Adding AI models to existing software through their APIs: choosing the right model, designing prompts and data flows, building the feature into your product's interface, and adding safeguards, logging and cost controls. LitSpark's AI integration services in Bengaluru help SaaS companies and enterprises ship generative AI features in weeks, without rebuilding their product.
Updated · LitSpark Solutions, Bengaluru
What We Add
GPT models inside your app, website or internal tools.
Summaries of calls, tickets and documents, and first drafts of replies.
Search that understands questions, not just keywords.
Route tickets, tag leads and sort documents automatically.
In-app assistants that help users complete tasks.
Pick the right use cases and models before building.
Who Uses It
AI features that justify a higher plan.
Suggested replies and ticket summaries.
AI inside ERP, CRM and internal portals.
Tagging, summaries and translation at scale.
How It Works
Where AI saves time or earns revenue.
A quick test on real data to prove value.
Feature built into your product with guardrails.
Quality, cost and speed measured.
Usage, cost and feedback tracked live.
Pricing
Price depends on the feature, data and safeguards needed. Typical bands:
Model usage is billed by the provider, and we set limits so costs stay predictable.
| Package | Budget | Timeline |
|---|---|---|
| AI PrototypeProve one feature on your data. | ₹50,000–1 lakh | 1–2 weeks |
| Production FeatureBuilt in, evaluated and monitored. | ₹1.5–4 lakh | 3–6 weeks |
| AI RoadmapSeveral features and a shared AI layer. | ₹3–10 lakh | 2–4 months |
Tech Stack
Why LitSpark
We integrate into your codebase and cloud.
We pick models on quality, cost and privacy, and can switch later.
Evaluation sets catch regressions before users do.
Caching, limits and dashboards keep bills predictable.
From the Blog
AI Automation6 min read
Explore how software teams are moving from AI code assistants to coding agents in 2026, and what engineering leaders should change in workflow, review, cost, and governance.
Read ArticleA prototype on your data usually costs ₹50,000–1 lakh. A production AI feature with evaluation and monitoring typically costs ₹1.5–4 lakh, plus model usage.
It depends on the task, cost and privacy needs. We test a few models on your data and recommend the best fit.
Yes. Most features connect through APIs and sit inside your existing interface.
We limit inputs, ground answers in your data, add checks and keep people in the loop for high-risk actions.
We use enterprise API settings that don't train on your data, and can use private or self-hosted models when required.
Let's talk
Tell us about your product. We'll suggest the AI feature most likely to pay off and a fixed price.