Jumpstart AI and Quantum Labs (JAQL) builds production AI for the industries that cannot afford to be wrong — banking, pharma, hospitals, government, defence. Two founders. Two decades each in regulated-enterprise execution. We ship in 21 days. We hold margin. We do not sell hype.
Most deep-tech companies are run by researchers learning enterprise. We are the inverse. Both founders are technically hands-on AND have lived the GTM trenches in regulated industries — banking, pharma, hospitals, government, regulators, educational institutions. We have sat on the buyer side of procurement. We have been audited by RBI, FDA, NHS, and the Big Four. We know what a CFO will sign and what a CISO will block.
JAQL builds production AI for the industries where wrong answers cost lives, jobs, or capital. We ship next-generation technology today — quantum-inspired, token-efficient, cognitively-grounded — but we earn the right to deploy it through margin discipline, regulatory fluency, and ROI you can defend in a board meeting. Papers and patents are byproducts of building. The product is the product.
"We don't sell research. We sell execution. The receipts are public."
— DR. NUPUR MUKHERJEE, FOUNDER
25 years across banking, pharma, and quantum. ex-MD Standard Chartered (Global Head, Data Analytics & ML). ex-Director Global Agentic AI, GSK — scaled the Centre of Excellence from 17 to 253 contributors in 16 months, £48M uplift. ex-Barclays. ex-HSBC QED. ex-VMware. Top 3 Quantum India Scholar 2025. PhD AI/Quantum and QED. CIMA UK World Rank 2. CPA Australia. NIST PQC alignment. Karnavati Quantum Hub Industry Mentor. Inventor of the patent-pending 7-cue STRESS framework.
Two decades of enterprise GTM in regulated verticals. Owns customer success, operational scale, and the path from pilot to enterprise contract. Buyer-side fluency in bank, pharma, and government procurement. Margin and CBA discipline beyond ARR — every pilot priced to defend gross margin and prove ROI before contract renewal. Land-and-expand motion architect. Owns the bank, MSSP, and government pilot pipeline. Specific customer references provided under NDA.
All-female founding teams received 2.3% of global VC in 2024 (Founders Forum Group). Female-founded companies generate 78¢ revenue per dollar invested vs. 31¢ for male-only teams (BCG, 2018). Mixed-gender teams deliver 2.5× the return multiple. JAQL is the structurally higher-return bet the data already backs — built on two decades of regulated-enterprise muscle.
We build for buyers who have to defend the purchase to a regulator, an auditor, and a board. Banking, pharma, hospitals, government, defence. We map every product to the relevant framework — DPDPA, RBI, IRDAI, CDSCO, FDA 510(k), MDR, DORA, NIS2, NESA, HIPAA, SOC 2, ISO 27001. Compliance is engineered in, not bolted on.
We bolt on in 48 hours. Security-adherent scale in 21 days. Cloud-portable across Azure, AWS, GCP. Quantum-portable across PennyLane and IBM Qiskit. Incumbents take 18 months. We do not. The difference is composition, not corner-cutting.
Every pilot is priced to defend gross margin before contract renewal. We optimise for ROI the customer can prove, not ARR a deck can flatter. CFOs sign because the cost-benefit analysis is honest. CISOs approve because the security posture is real.
Every product runs on JAQL — the cognitive-quantum platform fusing human expertise, AI, behavioural data, and quantum techniques. Token-efficient. Sovereign. Regulatory-native.
STRESSTrace — cognitive-quantum cybersecurity for boards, regulators, and the post-quantum decade. Indian Trademark 14075357. Seed round open.
Vibetrace.io — behavioural-signal × token-reduction layer. Launching 28 May 2026.
Quantama — quantum-inspired personalised longevity and health-optimisation engine. Funding open.
QAIScan — quantum-AI hybrid for medical imaging at hospital scale. Engineered for up to 1/100th per-scan compute cost on narrow-indication screening. CDSCO / MDR / 510(k) in progress. Radiologist-in-the-loop.
HIVA — corporate lending intelligence for SME credit underwriting. Riya Risk — operational risk and AI-cyber scoring for mid-market enterprises.
Mitra Darpan AI — Indian PSU compliance and citizen-grievance analytics. iParas — co-built civic-tech for participatory governance. CivIQiQ — Australia public-sector intelligence.
JAQL NV-7 — unmanned-systems intelligence for defence procurement. EMP-hardened beacon and NV-magnetometer architectures for rescue and detection.
Restraint is the moat. We publish what we won't build so customers, partners, regulators, and investors know exactly what they are buying — and what they are not.
Our behavioural-signal capabilities deploy only inside enterprise security, healthcare, and research perimeters where consent is explicit and PHI never leaves the customer boundary. We do not sell to social-media platforms, ad-tech, or location-tracking businesses.
Our defence work — JAQL NV-7, HIQTF quantum cryptography, NV-magnetometer rescue architectures — operates strictly within frameworks that keep a human in the decision loop. We turn down requests for fully autonomous targeting or kill-chain automation, regardless of the contract size.
QAIScan does not replace radiologists. STRESSTrace does not replace CISOs. HIVA does not replace credit officers. Our products are force-multipliers under licensed human review. This is a clinical-safety, regulatory, and liability decision — and a deliberate one.
Customer data, telemetry, and inference logs are never used to train external models, never sold, never shared with third-party AI providers without contractual PII redaction. Data posture is contractually enforced and externally auditable.
Our papers are SSRN preprints — published, citable, but not peer-reviewed. We say so on every paper page. Peer review for select papers is targeted for 2026–2027. We do not call preprints 'peer-reviewed' to inflate credibility.
Every claim on this site is verifiable: trademark numbers, paper IDs, former-employer references, framework alignments. Our 100× and 70% claims are workload-bounded with caveats on the relevant product pages. We publish what we do not yet know on /principles.
We do not sell to a regulated bank without ISO 27001 readiness and SOC 2 Type II on the roadmap. We do not sell to a hospital without CDSCO / MDR / 510(k) pathway in progress. Compliance is a product feature, not paperwork.
"If a deal requires us to compromise any of the above, we lose the deal. The list is the moat."
Token reduction in production AI workloads versus baseline transformer stacks. Measured in customer environments. Architecture references: RoPE (Su et al., 2021), MIT SEAL (arXiv:2506.10943).
Return on investment measured across deployed customer pilots. Calculated on defended gross margin, not ARR multiples.
Bolt-on time / full security-adherent scale time. Versus 18-month incumbent deployment cycles.
Revenue-per-dollar advantage of women-led teams over male-only teams (BCG, 2018). Mixed-gender teams: 2.5× return multiple. JAQL is the structurally higher-return bet.
Products live or in scheduled launch across seven verticals. Four continents of operating footprint.
Global medical-imaging-AI market by 2030. QAIScan targets the cost-per-inference layer no incumbent has solved.
Dr. Nupur's weekly newsletter on AI, quantum, cybersecurity, and the regulated-enterprise reality of deploying deep tech.
Hybrid framework reducing MRV uncertainty buffers by 30–40% across Verra VM0047 v1.1 and Puro.earth ERW Edition 2025. Provisional patent filed. Published on SSRN.
Read PDF →Trademarked framework combining Twin-Field QKD with orbital untrusted relays, PRF-deterministic basis selection, and behavioural AI. Provisional Patent IN/P/2025/XXXXX. Published on SSRN under BARDO AI.
Read PDF →First-principles derivation of the dipole-field limit and a hybrid 24-UAV swarm + EMP-hardened beacon architecture. Includes a published correction to earlier circulated analyses — scientific honesty as receipt. Published on SSRN.
Read PDF →All papers are SSRN preprints, not peer-reviewed publications. Peer review for select papers targeted 2026–2027. Reproducible code in appendices where applicable.
JAQL builds production AI for regulated industries — banking, pharma, hospitals, government, defence. We ship in 21 days, hold gross margin, and engineer compliance in from day one.
Dr. Nupur Mukherjee (Founder & CEO) and Krishan Sathyan (Co-Founder, Enterprise GTM & Operations). Two decades each across regulated-enterprise execution.
STRESSTrace is our cognitive-quantum cybersecurity platform for boards, regulators, and post-quantum risk. Indian Trademark 14075357. Currently raising seed.
QAIScan is a quantum-AI hybrid for hospital-scale medical imaging, engineered for up to 1/100th per-scan compute cost on narrow-indication screening. Radiologist-in-the-loop. CDSCO / MDR / 510(k) pathways in progress.
Vibetrace.io is the behavioural-signal × token-reduction layer powering JAQL deployments. Public launch: 28 May 2026.
RoPE-aware pruning combined with spectral importance scoring removes redundant LLM calls while preserving accuracy. Architecture references: RoPE (Su et al., 2021), MIT SEAL (arXiv:2506.10943). Production-measured.
Azure, AWS, GCP, on-prem, hybrid. Quantum-portable across PennyLane and IBM Qiskit.
48 hours bolt-on. 21 days to security-adherent scale.
Consumer surveillance, autonomous lethal systems, replacement of licensed professionals, training-data resale, fake peer review, deployments without compliance. Full list at /principles.
Engineered to DPDPA, RBI, IRDAI, CDSCO, FDA 510(k), MDR, DORA, NIS2, NESA, HIPAA, SOC 2, ISO 27001 — applied per vertical. ISO 27001 readiness and SOC 2 Type II on roadmap before bank shipments.
No. Our papers are SSRN preprints — published and citable but not peer-reviewed. Peer review for select papers is targeted for 2026–2027.
Founder-funded with revenue from production pilots. Seed / Series A open: STRESSTrace primary, Quantama live, Vibetrace.io launching May 2026. Dataroom available on request.
We bolt on in 48 hours. Security-adherent scale in 21 days. You pay only if the ROI clears your threshold.
Your data is encrypted in transit and at rest. Never sold. Never used to train external models. Portable across Azure, AWS, GCP, PennyLane, and IBM Qiskit on request.