Stop losing customers to AI-native competitors. A dedicated Apzzo engineering pod retrofits your existing web platform with LLM integrations, RAG search and automated workflows — shipped to production in weeks, not quarters.
Why AI modernization now
AI-native competitors are shipping features your platform can't match — not because your product is worse, but because your engineering capacity is already spoken for.
The bottleneck
Your in-house engineers are consumed maintaining legacy code, patching bugs and managing infrastructure. You want to launch AI features, but hiring a US AI engineer runs well over $200k a year and takes months to close.
The fix
We plug directly into your GitHub and Slack, engineer the AI microservices, and deploy to staging in weeks — without pulling your core team off the roadmap they already own.
The impact
Protect revenue at risk of churn, cut L1 support volume with RAG copilots, and open new market segments with intelligent workflow automation. We measure the baseline before we build.
What we build
We don't list twenty languages. These are the four AI capabilities that move the numbers for an established SaaS platform.
Turn unstructured PDFs, invoices, emails and CSVs into clean, validated database entries — with an exception queue for anything the model isn't confident about.
Grounded AI assistants built on your proprietary knowledge base, answering with citations so every response traces back to an approved source. Resolves L1/L2 tickets.
Machine learning pipelines that read customer telemetry and flag at-risk accounts before they cancel — with the reasoning attached, so your CS team can act on it.
Refactoring slow monolithic architectures into modular, serverless APIs built to carry high-concurrency AI workloads without your costs running away.
Portfolio
AI CX platform
We designed and engineered CogniSpot.ai — an AI-native CX product where merchants drop in a JavaScript snippet and get a shopping assistant, voice agent, ticket hub, and conversational analytics on one login. The live platform sells Free through Advanced plans, speaks 30+ languages, and is used by 350+ businesses.
AI SaaS product
We designed and engineered Fliter.ai — a browser-based speech platform where anyone can upload a file, pick a language, and receive a transcript by email. The same product now sells subscriptions, speaker identification, AI summaries, and a five-module media suite.
PropTech
FixerFlip is a live product from Fixer Flip LLC. Apzzo engineered it in Expo so iOS, Android, and the web app at app.fixerflip.ai share one codebase. Investors search fixer-uppers, run FlipScore™ deal analysis, calculate ROI and ARV, preview renovations with AI, and connect with contractors, agents, and lenders — without bouncing between Zillow, Excel, and bid emails.
EdTech
PrepZap is a live learning product from 27Two Creative LLP in Gurugram. Students generate unlimited humanities and commerce practice — haikus, memes, flashcards, and quizzes — aligned to CBSE / NCERT and useful for CUET, using cognitive science instead of another PDF dump.
AI receptionist
CSAgentIQ is a live AI receptionist for home services. HVAC, plumbing, electrical, roofing, and garage-door shops get 24/7 voice, chat, and WhatsApp coverage, smart appointment booking, and a field-service admin at fsm.csagentiq.com — without hiring a night desk.
The delivery process
No discovery phase that runs for a quarter. Every step is timeboxed and ends in something you can look at.
Step 1
Days 1–3
We inspect your application, API endpoints and database bottlenecks to pinpoint the highest-ROI AI integration — and rule out the ones that aren't worth building.
Step 2
Week 1
We build a functional proof of concept and document the data schemas, latency budgets and security boundaries it has to live inside.
Step 3
Weeks 2–4
The pod builds the complete feature with test coverage (Cypress / Playwright), evaluations, guardrails and CI/CD pipelines wired in.
Step 4
Weeks 5–6
We deploy to your live cloud infrastructure, hand over complete documentation, and train your internal developers to own it.
Send us your product URL. Our senior architects analyse your platform and return a custom PDF report within 3–5 business days containing:
Zero sales pitch. Actionable engineering analysis, under mutual NDA if you want one in place first.
Onboarding & governance
Most of the delay in outsourced engineering is procurement, not engineering. Here's the first week, concretely.
First week
Day 1
Mutual NDA executed and GitHub repository read-access granted.
Day 2
Shared Slack channel created, Jira / Linear board synchronised.
Day 3
Architecture alignment session with your CTO or lead architect.
Day 5
First working code commit in an isolated staging sandbox.
Security & IP
SOC 2–aligned practices
Access logging, least-privilege repository access and background-checked engineers. We'll complete your vendor security questionnaire during onboarding.
Zero Data Retention AI configs
Model providers configured so your data is never retained or used for training. Self-hosted models where residency requires it.
100% work-for-hire IP
Everything we write is yours on assignment — code, prompts, evaluations and documentation.
Start with the free architecture teardown. You'll see exactly where AI fits in your platform, what it costs, and how long it takes — before you commit to anything.
Mutual NDA available before you share anything · 100% IP assignment · Direct access to the engineers doing the work