Press & Media
NAIQ is an early-stage Indian AI company building long-horizon intelligence systems, with analyst-led Industrial AI services available today and broader deep-tech research in active development.
Industrial AI is commercially live. Quantum, Cognitive, and Collaborative Intelligence research tracks are pre-revenue.
Two tracks. One mission. One accountable decision system.
NAIQ at a glance
Everything a journalist, analyst, or investor needs to orient quickly.
| Legal Name | NAIQ Health Tech Private Limited |
| Founded | 2024 |
| Headquarters | Raipur, Chhattisgarh, India |
| Website | naiq.in |
| Industry | Artificial Intelligence · Industrial Technology · Deep Tech |
| Company Stage | Early-Stage · Pre-Revenue Overall |
| Live Offering | Industrial AI — Analyst-Assisted Delivery |
| Research Tracks | Quantum Computing, Quantum Sensing, Cognitive Science, Mathematics, Collaborative Intelligence |
| Engagement Model | NDA signed on day one, always |
| Press Response | Within 24 hours on business days |
Industrial AI — commercially available
NAIQ's first product is live, deployable, and available to enterprise clients today through an analyst-assisted model.
Analyst-Assisted Industrial Intelligence
NAIQ's current delivery model is intentional, not transitional. Certified industrial AI analysts receive your operational data — production logs, maintenance records, downtime histories, energy consumption data, SCADA outputs — examine it using NAIQ's intelligence frameworks, and return structured deliverables: anomaly reports, predictive maintenance schedules, throughput optimisation recommendations, and ROI projections.
The analytical depth you receive today is the same depth a fully autonomous platform would provide. The difference is in who executes the inference loop — a trained human analyst using NAIQ's systems, rather than a fully automated pipeline. Full autonomous productisation is in active development. This model lets enterprises engage with serious industrial intelligence now, without waiting for a software release cycle.
Pre-Revenue Research Tracks
In parallel with Industrial AI operations, NAIQ maintains active research programmes in five long-horizon domains. None of these tracks are commercially live; all are in genuine pre-revenue research development.
The market moment
Why accountable, domain-specific industrial AI is one of the most important bets an enterprise can make today.
General AI performs at median. Domain AI performs at the frontier.
Large general-purpose models are trained on everything, which means they are optimised for nothing in particular. An industrial AI system trained specifically on the failure signatures of a cement kiln, the anomaly patterns of a pharmaceutical packaging line, or the load curves of a smart-grid substation will outperform a general model on those tasks — every time. Domain specificity is not a limitation. It is the frontier.
The real scarcity is accountability, not intelligence.
In the LLM era, intelligence itself has become abundant and shared. What remains rare — and what determines whether AI moves the world — is the architecture that makes intelligence accountable. Explainable, auditable, bias-monitored, human-overseeable. Enterprises cannot deploy systems they cannot justify. NAIQ builds accountability in from day one, not as an afterthought.
Service-led deployment is a strategic advantage, not a weakness.
Going to market with analyst-assisted delivery before full software automation is a deliberate choice rooted in enterprise reality. Most industrial operations are not ready for a fully autonomous AI pipeline on day one. They need a trusted intelligence partner who can engage with their existing systems, data, and operational culture — and deliver real results while the full platform matures. That is exactly what NAIQ's Phase X model provides.
India's industrial base is one of the largest underserved AI markets on earth.
India's manufacturing, energy, logistics, and healthcare operations sectors are among the world's largest — and among the least penetrated by serious industrial AI. Built from Raipur, for the world, NAIQ is positioned to serve this market with systems designed for its linguistic diversity, resource constraints, legacy infrastructure realities, and operating scale. The transformation is not arriving slowly. It is arriving now.
Where NAIQ operates
Six deployment-ready use cases covering the critical intelligence needs of industrial operations today.
Predictive Maintenance
Sensor fusion and anomaly detection across rotating equipment, electrical systems, and process machinery — identifying failure signatures days or weeks before breakdown. Eliminate unplanned downtime, reduce emergency repair costs, and shift maintenance from scheduled intervals to condition-based intelligence.
Computer Vision Quality Control
Sub-millimetre defect detection at production line speeds — surface anomalies, dimensional variance, assembly errors — deployed without slowing throughput. Reduces human inspection fatigue, improves consistency, and provides full audit trails for compliance and customer delivery.
Production Line Optimisation
Real-time throughput analysis against production targets, with AI-generated scheduling recommendations that account for machine health, operator availability, and order priorities. Identify bottlenecks before they compound and simulate the output impact of scheduling decisions before committing them.
SCADA / PLC Integration
An intelligence overlay on existing control architectures — no rip-and-replace of your SCADA or PLC infrastructure. NAIQ connects to existing data streams and returns enriched operational intelligence: anomaly alerts, trend forecasts, and decision recommendations delivered back into your existing operator interfaces.
Energy & Waste Optimisation
AI-driven load balancing, peak-demand forecasting, and waste-stream analysis across manufacturing and operational facilities. Reduce energy expenditure per unit of output, identify waste generation patterns invisible to manual review, and model the ROI of operational changes before implementing them.
Custom ROI Roadmap
Every NAIQ engagement begins here. Before any recommendation, forecast, or deployment, our analysts produce a scoped, costed ROI assessment specific to your operational context. You understand the financial case, the implementation timeline, and the measurable outcomes before committing to anything further. Transparency from day one.
Early signals, honest metrics
NAIQ is early-stage and pre-revenue overall. These indicators reflect genuine operational activity — not vanity metrics.
Completed
Underway
Engaged
Operational
Active
Placeholder fields are updated as milestones are reached. NAIQ does not publish speculative metrics. Journalists and investors are encouraged to request a current briefing document directly from the press team.
The mind behind the mission
Biography, credentials, speaking topics, and interview themes for media use.
Resham Raj Shivwanshi is the Founder and Director of NAIQ Health Tech Private Limited. He holds a PhD from NIT Raipur in artificial intelligence, deep learning, computer vision, and medical image analysis, and received the IEEE Best Paper Award at an international conference in Poland in 2023. He has held positions at IIT Bhilai as Principal Project Associate, at Turing as an RLHF contributor on frontier large language models, and at Woxsen University as Assistant Professor at the School of Technology. He founded NAIQ on a single conviction: that in the era of abundant AI, the decisive challenge is not intelligence — it is accountability.
Resham Raj Shivwanshi's career has moved in a deliberate arc across the full depth of modern AI — from foundational academic research in medical image analysis and computer vision at NIT Raipur, to applied frontier work on reinforcement learning from human feedback at Turing, to building NAIQ from the ground up in Raipur, Chhattisgarh. His doctoral thesis explored deep learning architectures for medical imaging, earning recognition at IEEE's international programme in Poland in 2023. At IIT Bhilai, he served as Principal Project Associate, contributing to applied research at one of India's newest premier technical institutions. His work in RLHF at Turing placed him at the operational frontier of large language model alignment — directly shaping how frontier models learn from human judgment. At Woxsen University, he served as Assistant Professor, combining industry research with academic contribution.
He founded NAIQ on the observation that as intelligence becomes abundant and commoditised, the architecture that makes intelligence accountable becomes the genuine competitive advantage. NAIQ's Industrial AI is the first expression of this conviction — a deployable system that unites human judgment and machine inference in a single, auditable decision loop. His longer-horizon ambition is Collaborative Intelligence: not a single AI above everything, but an interconnected fabric of accountable systems that amplify human judgment without replacing human responsibility.
Why explainability, audit trails, and human-oversight architecture are the defining technical challenge for enterprise AI in the 2020s.
Deploying domain-specific intelligence in India's manufacturing, energy, and healthcare operations sectors — constraints, opportunities, and architecture.
The mechanics and philosophy of reinforcement learning from human feedback — what it means for alignment, accountability, and the future of human-machine collaboration.
The structural and cultural challenges of building a serious deep-tech company outside India's traditional startup centres, and why it matters for the country's AI future.
From medical image analysis to quality control on production lines — practical architecture for deploying computer vision in high-stakes operational environments.
NAIQ's long-range research vision — the nature of machine reasoning, the limits of current AI architectures, and what it would mean to build genuinely accountable, context-aware decision systems.
Logos & brand assets
All assets are free for editorial use with attribution. Contact press.media@naiq.in for custom usage requests.
Before you use NAIQ brand assets
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- Maintain clear space equal to the cap-height of the "N" on all sides of the logo.
- Use the white-pulse logo on dark backgrounds; use the ink or navy mark on light backgrounds.
- Do not use NAIQ brand assets to imply endorsement, partnership, or investment without written permission.
- When in doubt, email us. We respond within 24 hours on business days.
Press documents & materials
Contact our press team to receive any of the following documents. We prepare tailored versions for your specific editorial or investment context.
Colour palette
Standard company description
For use in articles, features, and press releases with attribution to NAIQ.
NAIQ Health Tech Private Limited is an early-stage Indian AI company building long-horizon intelligence systems, with analyst-led Industrial AI services available today and broader deep-tech research in active development. Founded in 2024 and headquartered in Raipur, Chhattisgarh, NAIQ's Industrial AI covers predictive maintenance, computer vision quality control, production line optimisation, SCADA integration, and energy and waste optimisation — deployable across manufacturing, healthcare operations, logistics, energy, and smart-city infrastructure. Every NAIQ engagement begins with a scoped ROI assessment and an NDA signed on day one. For more information, visit naiq.in or contact press.media@naiq.in.
Official channels
Core narratives for coverage
These messages reflect NAIQ's current positioning and may be cited with attribution.
Common questions
Answers to the questions journalists, investors, and enterprise contacts ask most often.
NAIQ builds the architecture where human judgment and machine inference work as one accountable, auditable decision system. In practical terms today, this means Industrial AI for manufacturing, healthcare operations, logistics, energy, and smart-city infrastructure, delivered through an analyst-assisted model. NAIQ also maintains active long-horizon research in Quantum Computing, Quantum Sensing, Cognitive Science, Mathematics, and Collaborative Intelligence — though these tracks are pre-revenue and not yet commercially available.
NAIQ's Industrial AI is commercially live and available to enterprise clients through an analyst-assisted delivery model. Clients submit their operational data — production logs, maintenance records, energy consumption data, SCADA outputs — and NAIQ's analysts return structured deliverables: anomaly reports, predictive maintenance schedules, throughput optimisation recommendations, and ROI projections. The analytical depth is equivalent to what a fully autonomous platform would produce. Full software automation of this pipeline is in active development. All other research tracks (Quantum, Cognitive Science, etc.) are pre-revenue.
NAIQ is pre-revenue overall — meaning the company has not yet recognised commercial revenue at the company level. Industrial AI services are commercially available and priced, and the company is in active commercial engagement. Revenue recognition will follow as signed commercial engagements are executed. NAIQ is transparent about this stage because we believe investors and journalists deserve an honest picture, not a misleading framing. Pre-revenue at this stage, for a company of NAIQ's profile and technical depth, is a stage — not a limitation.
NAIQ's Industrial AI is applicable across manufacturing (discrete and process), healthcare operations (hospital and clinical logistics, not clinical diagnostics), logistics and supply chain, energy (power generation, grid management, renewables), and smart-city infrastructure. The common thread is operational complexity, data-richness, and the need for accountable, domain-specific intelligence rather than general-purpose AI outputs.
NAIQ is open to conversations with aligned angel investors and strategic believers in industrial AI, deep tech, and long-horizon intelligence systems. We are not conducting a formal fundraise at this stage and are not in active pitch mode. Our priority is building — operationally and technically. If you are an investor whose thesis aligns with what NAIQ is building, we welcome a direct conversation. Reach out via press.media@naiq.in and indicate your investment focus in the subject line.
Email press.media@naiq.in with your name, publication, the angle you are covering, and your deadline. We aim to respond within 24 hours on business days. For urgent fact-checks, please include "URGENT" in your subject line. Resham Raj Shivwanshi is available for interviews, written Q&A, and expert comment. We will not confirm or deny information we cannot verify, and we will always correct the record if something inaccurate is published about NAIQ.
All three, sequentially and simultaneously. NAIQ began with research convictions about accountability architecture in AI. It is currently operating as a services firm — delivering real industrial intelligence to clients through its analyst-assisted model. And it is actively developing into a product company — building the software infrastructure that will fully automate what analysts currently execute manually. The long-horizon research into Quantum Computing, Cognitive Science, and Collaborative Intelligence reflects the scientific foundation the company intends its future products to rest on. The honest answer is that NAIQ is an early-stage deep-tech company executing a services-to-product transition while simultaneously advancing its research agenda.
It is NAIQ's core architectural principle: the highest-value AI systems are neither fully autonomous — replacing the human — nor merely assistive — waiting for commands. They are designed so that machine inference and human judgment operate in one shared, auditable decision loop, each correcting and improving the other. The model surfaces patterns, forecasts, and options at machine speed; the human contributes context, accountability, and the final call; and every decision is logged so the system gets measurably better over time. In short, collaborative intelligence is AI built to make human decisions more accurate and more accountable — not to remove the human from them. NAIQ builds toward that architecture, one domain at a time.
NAIQ is open to the right conversation.
We are not conducting a formal fundraise. We are building. But we believe that the right angel investors and strategic believers in industrial AI, deep tech, and long-horizon intelligence systems are genuine partners, not just capital sources. If you are early-stage in your conviction, comfortable with pre-revenue companies at the frontier of serious technical work, and interested in India's industrial AI opportunity — we would welcome a quiet, substantive conversation.
There is no pitch deck at the door. There is a body of work, a technical founder, a live product, and a long-range research vision. If that interests you, reach out directly.
Begin a ConversationGet in touch
For press enquiries, interview requests, fact-checking, or asset downloads — contact the press team directly. We respond within 24 hours on business days.
Press & Media Enquiries
Resham Raj Shivwanshi
Founder & Director, NAIQ Health Tech Private Limited
Raipur, Chhattisgarh, India