AI systems that ship, not just demos. We build production-grade AI agents, voice apps, and data pipelines — backed by 2+ years running distributed systems at 1K+ req/sec with 99.9% uptime.
AI Resume Builder
AI Interview App
AI Illustrator
Web Scraper & Leads5K+ Users served in production
0K+
requests / sec in production
0.0%
uptime over 6 months
0%
latency cut (800ms → 320ms)
0K+
background jobs / day
Four products built end to end — voice AI, agentic workflows, and the backend that keeps them running.
Voice-to-Voice App
Talk through your career and walk away with a finished resume. A voice agent interviews you, pulls out the achievements that matter, and writes ATS-ready bullet points — no blank page, no formatting fight.
Real-Time Voice Platform
Screen every applicant without booking a single call. Full audio-to-audio interviews run on open-source models plus ElevenLabs voices, then score answers and return structured feedback while your team sleeps.
Agentic Video Generation
Ask a question, get an explainer video. Agents research the topic, script it, and render a clean illustrated walkthrough — turning documentation and training material into something people actually watch.
Data Extraction Engine
Paste a URL, describe what you need, get clean structured data back. Doubles as a lead-generation engine that builds qualified prospect lists from any site — hours of manual copy-paste reduced to one request.
IoT & ML Platform
Know a machine is failing before it fails. Telemetry streams off your fleet over MQTT, ML models flag the anomalies, and the team gets a warning while there is still time to act — instead of an outage report afterwards.
Agentic RAG Chatbot
Ask your financial data questions in plain English. A retrieval pipeline grounds every answer in your uploaded datasets, agents handle the multi-step reasoning, and role-based access keeps sensitive figures with the people cleared to see them.
“They rebuilt our platform as six services that scale independently, and our p99 latency dropped from 800ms to 320ms. The system has held 99.9% uptime since.”
Engineering lead
Enterprise platform client
Systems that do the work, not just answer questions.
Put the repetitive work on autopilot — agents that research, decide, and act across your tools instead of another dashboard someone has to check.
Drop a proven assistant into your product, or get one built on your own data and rules. Either way it answers from your content, escalates when it should, and leaves a transcript your team can audit.
Conversations that happen without your team on the call: audio-to-audio agents that screen, qualify, and hand over with a written summary.
Answers grounded in your own documents and data, so the model stops guessing and your team stops double-checking it.
Know whether a change made the model better or worse. Test suites, scoring, and regression checks around your prompts and agents, so shipping stops being a guess.
Move it, clean it, then actually learn something from it.
Move between databases, hosts, or cloud providers without a maintenance window that scares your customers — dual-write, verify, then cut over with a rollback path the whole way.
Split the parts that need to scale from the parts that do not, one service at a time, while the product keeps shipping. We did exactly this at 1K+ req/sec.
Ingestion that keeps up — streaming, batch, and scraped sources landing clean, deduplicated, and queryable with replay when something breaks.
Already sitting on data? We turn it into answers — where users drop off, which cohorts stay, what actually drives revenue — with dashboards your team reads instead of ignores.
Qualified prospect lists built from public sources on a schedule, enriched and deduplicated, landing straight in your CRM rather than a spreadsheet somebody maintains by hand.
The thing your customers actually touch.
Interfaces designed and built together, so what gets designed is what gets shipped — no handoff gap, no compromise at implementation.
One codebase, both stores, native where it counts. Offline handling, push, and release pipelines set up before launch rather than bolted on later.
The unglamorous work that keeps the rest standing up.
Services that scale independently and survive traffic spikes, with caching, queues, and retries handled before launch rather than after the incident.
Ship daily without ceremony: containerised builds, automated pipelines, and deploys that take minutes instead of an afternoon.
Uptime you can put in a contract — monitoring, alerting, circuit breakers, and graceful degradation so failures stay contained.
Our stack
The stack behind every build — from first schema through to a containerised, monitored deployment.
Most conversations start with one of these. Type your own at the bottom and it carries straight into WhatsApp — no form, no wait.
What can you actually build for us?
Most of what we ship falls into four areas:
We're stuck on a monolith that falls over under load. Can you help?
Yes — that is the exact migration we ran at Tibil. One monolith became six independently deployable services handling 1K+ requests/sec, with p99 latency down from 800ms to 320ms and 99.9% uptime since.
We already have a lot of data but no idea what it's telling us.
Then we start there. We map what you collect, clean up what is unreliable, and put dashboards in front of your team that answer the questions you actually ask — where users drop off, which cohorts stay, what drives revenue.
Opens WhatsApp with your message ready to send.
Ritesh Chauhan
Founder · AI Full Stack Engineer
Where we have worked
HireSense.ai
AI Full Stack Engineer
2026-Present
Tibil Solutions
Backend Engineer
2025-2026
Dhee Coding Lab
Backend Developer
2024-2025
We build AI products that hold up in production. That means voice agents that respond in real time, retrieval pipelines that return grounded answers, and the unglamorous backend work underneath — queues, caching, retries, and monitoring — that keeps them running when traffic arrives.
The foundation is distributed systems. Decomposing a monolith into six deployable services handling 1K+ requests/sec. Cutting p99 latency from 800ms to 320ms with Redis caching and index tuning. Processing 10K+ background jobs a day without blocking a single API response.
Every project is designed before it is written — LLD, HLD, and the design patterns that make code survive its second year. Circuit breakers, idempotency keys, graceful degradation. That is the difference between a demo that impresses and a system that earns 99.9% uptime.
Clear costs, no hidden fees. Work with us monthly, or scope a single project with a fixed price.
We map the problem, the data, and the success criteria before a line of code is written.
You get working software in weekly increments — not a status update, a running system.
Deployed, containerised, and monitored on your infrastructure with CI/CD in place.
Work directly with the engineer building your system. AI and backend engineering for teams who need it in production, not in a slide deck.
One flat monthly rate for continuous AI and backend engineering. Ideal for teams shipping an AI product and iterating fast.
Fixed-scope delivery for a defined build — an AI agent, a data pipeline, or a backend migration.
5K+ Users served in production
48h → overnight
The voice interview agent screens candidates around the clock. What used to take our team a week of calls now happens overnight.
Talent lead
AI recruitment client
10K+ jobs/day
Ten thousand background jobs a day move through the queue and our API response times never went above 200ms.
Platform manager
Enterprise platform client
99.9% uptime
Circuit breakers and graceful degradation meant our last outage stayed contained to one service instead of taking the platform down.
Head of engineering
Enterprise platform client
−25% infra cost
Infrastructure costs came down a quarter after the caching layer and query work. The savings paid for the engagement.
CTO
Enterprise platform client
5K+ users
Twenty REST APIs serving five thousand users, delivered clean and documented. Zero post-launch bugs reported.
Delivery manager
Software services client
30% faster loads
Code splitting and asset work cut our initial load time by a third, and three features shipped in a six-week engagement.
Product lead
Web platform client
A focused agent or integration usually ships in 2-3 weeks. A full voice-to-voice platform or multi-service backend runs 1-2 months. You'll get a specific estimate after we scope the problem together.
Talk through what you are building. We will tell you what it takes, what it costs, and whether we are the right fit.
Schedule Now
What it takes to get audio-to-audio latency low enough to feel like conversation — streaming STT, model selection, and the buffering tricks that hide the round trip.
Aug 6, 2026 · By Ritesh Chauhan
Jul 22, 2026 · By Ritesh Chauhan
Jul 1, 2026 · By Ritesh Chauhan
Send a few details and we will come back within one working day with an honest answer on scope, cost, and whether we are the right fit.
Book a 30-minute call. No pitch — we will map the problem and tell you what it takes.
Email to arrange a time