The operating system for sovereign AI in India.
BiltIQ AI is the operating system for sovereign AI in India — the layer around the model that turns raw capability into a system a regulated enterprise can actually run. Engineering-led from day one, bootstrapped since 2021, and built on one conviction: your most valuable data should never have to leave your building to be useful.
Founded in Jamshedpur in 2021. Engineering-led from day one.
Founder · Aarna Tech Consultants Pvt. Ltd.
Harish leads BiltIQ AI's engineering practice — on-premise LLM deployment, agentic-system architecture, and GPU infrastructure for regulated Indian enterprises. Building since 2021 in Jamshedpur.
Co-Founder · Aarna Tech Consultants Pvt. Ltd.
Sonali drives BiltIQ AI's product strategy and operations — engagement design, customer success, and the productisation of services into the ATC suite.
Every industry we entered had the same problem — not a lack of AI, but a lack of AI that actually worked inside the business.
“We didn't set out to be anti-cloud. We set out to build AI that organizations could actually trust with their most sensitive operations. On-premise was the only honest answer.”
We don’t want to be just another AI company. We want to be a genuine one — giving people real intelligence over their own knowledge, not a rephrasing of the public internet, and doing it in a way that keeps their data private and their intellectual property theirs.
Every serious Indian institution should be able to run AI that is grounded in its own data, owned outright, and accountable — without renting its most valuable information to someone else’s cloud. We’re building the platform that makes that the default, not the exception.
How that thesis becomes a running system: the AI transformation path.
We don't speak in projections. These are the numbers we've built to.
Every engagement follows a structured methodology — from infrastructure audit to production deployment to ongoing maintenance.
We start by understanding your existing infrastructure, data landscape, compliance requirements, and operational workflows. No generic questionnaires — a real engineering assessment of what you have, what you need, and what’s the shortest path to production AI.
We design the complete system architecture — GPU provisioning, model selection, RAG pipeline design, agent workflows, and application layer. Every decision is documented. You approve the architecture before a single line of code is written.
Development, integration, testing, and deployment — all targeting your on-premise infrastructure. Most ATC products deploy in days, not quarters. Custom systems take 4–12 weeks depending on scope. Air-gapped environments are standard capability.
We don’t deploy and disappear. Ongoing monitoring, model updates, performance optimization, and support are built into every engagement. Your AI stack gets better over time — and we maintain it so your team doesn’t have to build that capability from scratch.
Every decision we make — from model selection to deployment architecture to pricing — is filtered through these three commitments.
Your data never leaves your servers. Every system we build runs on your infrastructure — air-gapped if needed. We don’t offer a cloud option because we don’t believe your sensitive data should be anywhere but your premises.
Our agents don’t start autonomous. Every agent begins with human review (T1). After 95% agreement over 200+ decisions, it earns T2 status — auto-execution with notification. Critical actions remain permanently human-reviewed.
We don’t hand off hardware to one vendor, software to another, and maintenance to a third. We architect, deploy, and maintain the complete stack — GPU servers through application software through ongoing operations.
This isn't a preference — it's an architectural position rooted in how regulated industries actually operate.
Patient records, financial transactions, student data, production telemetry — your most sensitive data stays on your servers, inside your firewall, under your governance.
Cloud AI costs escalate with usage — the more successful the system, the more expensive it becomes. On-premise is a capital investment with a declining marginal cost.
When your AI runs on the same network as your applications, inference latency drops to single-digit milliseconds. For real-time voice and video, this is the difference between usable and unusable.
You own the code. You own the models. You own the infrastructure. If you ever want to part ways with us, you keep everything — every line of code, every fine-tuned model, every byte of data.
30-minute architecture consultation. We'll assess your stack, recommend a deployment path, and give you a real TCO estimate.
Recognized by the Department for Promotion of Industry and Internal Trade, Government of India.
Member of NVIDIA’s Inception program for AI-native startups — access to GPU resources, technical training, and go-to-market support.
Architecture designed for compliance with India’s Digital Personal Data Protection Act, 2023. Data sovereignty by design, not by policy.
Five layers. All on your premises. All maintained by us.
GPU servers, networking, cooling — we specify, procure, or help you configure the hardware
LLMs (Qwen3, DeepSeek-R1), embeddings, vector DB, RAG pipelines, MCP protocol
Agentic systems — autonomous task execution with progressive autonomy and human governance
ATC suite — Manthan, Quest LMS, Campus, Chat, Voice, Flow, Connect, Social, CMS, Ops
Monitoring, updates, support, optimization — we maintain your AI stack, ongoing
Each pillar is a deep capability — not a feature list.
Multi-agent systems with progressive autonomy on your infrastructure.
Explore →Full-stack AI applications — LLM, RAG, MCP, fine-tuning.
Explore →Subscribe to agents, not SaaS. Personal, team, enterprise tiers.
Explore →GPU provisioning, multi-model management, infrastructure operations.
Explore →RAG pipelines, knowledge bases, multi-channel agents.
Explore →ASR, TTS, voice agents, video analysis. Sub-200ms latency.
Explore →A small, senior team that builds production AI systems — not slide decks about AI.
Runs BiltIQ AI's delivery programs end to end — scoping engagements, tracking every deployment from kickoff to handover, and keeping timelines honest.
Still hands-on in the field as an FDE, so every plan on the board is one that's been executed first-hand.
Leads the forward-deployed engineering team — owning architecture, code quality, and the technical shape of every client AI deployment.
Splits time between the client's site and the codebase so what ships in production is what the client actually needs.
Embeds with client teams to deploy, integrate, and tune BiltIQ AI systems inside their existing infrastructure.
Bridges the gap between the platform and the realities of a live enterprise environment.
Builds the software layer of BiltIQ AI's products — from production front-end code to the interfaces that put AI capability into daily use.
Believes good engineering is measured by what users can do with it, not by the stack behind it.
Creates AI-generated video and visual media for BiltIQ AI's products, marketing, and client work — from brand films to product demos.
Brings the same design discipline to a generative pipeline as to a hand-crafted frame.
Deploys and scales BiltIQ AI systems across cloud and hybrid environments — taking ATC products from installation to daily use in client workflows.
Focused on deployments that perform well and stay maintainable after handover.
Builds AI-driven features into client-facing products — RAG pipelines, agent workflows, and the services that connect them.
Prioritises solutions that are testable, observable, and easy to hand over.
Owns the LLMOps layer — CI/CD, containerisation, model serving, and server operations for BiltIQ AI's on-premise and cloud deployments.
Measures success in uptime, reproducible builds, and models that stay served without a hero.
Supports client AI deployments end to end — setup, integration, and fixes — while learning the full BiltIQ stack in the field.
Brings fresh eyes and a bias for shipping.
Deploys and customises BiltIQ AI systems at client sites, with an emphasis on correctness, testing, and clear documentation.
Makes sure every deployment is one the client's own team can understand and operate.
Every system we build runs on your infrastructure. Built for DPDP obligations by architecture. Zero cloud dependency.
Every system we build runs on your infrastructure. Book an assessment — we’ll tell you what your workload actually needs.
Your Data. Your Premises. Your AI.
