AI & Machine Learning Company in Delhi

Sector compliance is the line between a quick Delhi NCR pilot and a full production system. A scoped AI proof of concept is a six to ten week engagement covering data audit, a baseline model, and a hosted demo on AWS ap-south-1 or Azure Central India. A custom production ML model (fraud scoring, credit decisioning, dynamic pricing, claims triage, document extraction) adds MLOps, monitoring, and a DPDPA-aligned model card with sector-specific compliance artefacts. Full production AI systems layer on RAG, multiple models, fine-tuning, and Indic-language coverage. Delhi NCR sits between Bangalore and Mumbai on cost because of the Paytm, Zomato, MakeMyTrip, and IIT Delhi talent premium. We invoice in INR with GST or USD per client preference and prefer Festpreis over open T and M.

The IndiaAI Mission was approved by the Union Cabinet in March 2024 with a USD 1.25B (INR 10,372 crore) allocation across seven pillars: IndiaAI Compute Capacity (10,000+ GPUs available at subsidised rates via the IndiaAI Compute Portal), IndiaAI Innovation Centre (foundation models including the Indic LLM workstream), IndiaAI Datasets Platform (AIKosha), IndiaAI Application Development Initiative, IndiaAI FutureSkills, IndiaAI Startup Financing, and Safe and Trusted AI. Our discovery phase checks whether your project qualifies for compute subsidy, dataset access, or grant funding under one of these pillars. For startups and SMBs the Application Development Initiative grants and the FutureSkills upskilling subsidies are often material. For public sector buyers, the Mission's framework shapes GeM RFP language and Class-1 local supplier preferences. Final eligibility sits with the IndiaAI Mission Secretariat at MeitY.

Yes. We ship fraud detection, UPI risk scoring, AML transaction monitoring, credit decisioning, KYC document extraction, video KYC, and collections AI for Delhi NCR fintechs including the Paytm and PB Fintech pattern. For RBI-regulated clients (PA-PG, NBFC, payment system operators, prepaid wallet issuers) we stay inside Indian regions (AWS ap-south-1, Azure Central India), apply RBI Cybersecurity Framework controls, the Digital Payment Security Controls master direction, and the Digital Lending Guidelines (mandatory Key Fact Statement, look-through to the lender, cooling-off, and cap on default loss guarantees from June 2023), and produce the System Audit Report (SAR) and VAPT evidence pack through a CERT-In empanelled auditor that RBI inspectors actually accept. Output logs feed existing SIEM and the RBI CERT-Fin incident reporting workflow with the 2 to 6 hour escalation window.

Bhashini, the National Language Translation Mission, is a Delhi-led MeitY programme that supports translation, speech recognition, and TTS across the 22 official Indian languages listed in the Eighth Schedule of the Constitution. Our Indic-language AI builds use AI4Bharat models (IndicTrans2, IndicBERT, IndicBART, IndicConformer for ASR, IndicTTS) developed at IIT Madras and available under permissive licences, plus fine-tunes on Bhashini's open datasets via AIKosha. For higher-quality production deployments we layer Whisper plus IndicWhisper for ASR, IndicTrans2 plus NLLB-200 for translation, and SeamlessM4T for speech-to-speech. Code-mixed Hindi-English (Hinglish) handling is a frequent ask: we maintain a benchmarked code-mix dataset and fine-tune accordingly. Bhashini's ULCA (Universal Language Contribution API) is the integration surface for govt clients and the integration playbook is well documented.

When a project requires genuine research (novel architectures for satellite imagery, rare-event detection in financial transactions, multi-agent simulation for defence wargaming), we scope collaborations with IIT Delhi's Yardi School of AI, IIIT Delhi's Centre for Artificial Intelligence, or DRDO's Centre for Artificial Intelligence and Robotics (CAIR — primarily Bangalore but with Delhi NCR coordination at DESIDOC) rather than overselling in-house novelty. Our core team handles applied engineering, MLOps, and productionisation, which is where most Delhi AI projects actually stall after the prototype. For standard work (RAG, fine-tuning, classical ML, vision on known architectures) no academic partner is needed. We will tell you which bucket your problem fits into and have introduced Delhi NCR clients to IIT Delhi industry programmes and the IndiaAI Innovation Centre cohorts when the fit and budget align.

The MeitY advisory of 1 March 2024 initially required intermediaries and platforms to obtain explicit government permission for under-tested or unreliable AI models before deployment, label generative AI outputs that could be used for misinformation, and ensure no bias or discrimination in model outputs. After significant industry pushback, MeitY issued a revised advisory on 15 March 2024 that removed the prior-permission requirement, retained the labelling requirement, and clarified that the obligation falls on the platform. Our builds ship with permanent metadata-based watermarking aligned with the C2PA standard, visible labels on generative AI outputs, bias and fairness reviews against representative Indian subgroup data (linguistic, regional, caste/community, gender), and a complaint-handling SOP per the DPDPA Grievance Officer model. We track subsequent MeitY clarifications and the DPDP Rules notification path so the compliance pack is current at go-live, not at the original advisory date.

We default to AWS ap-south-1 (Mumbai), Azure Central India (Pune), and GCP asia-south1 (Mumbai), with multi-region active-active to AWS ap-south-2 (Hyderabad, opened 2022) or GCP asia-south2 (Delhi NCR, opened 2021). For government and defence-adjacent workloads we use MeitY-empanelled sovereign clouds on the GI Cloud (MeghRaj) framework including CtrlS, ESDS, Sify, Yotta, and Netmagic, with data centres certified to STQC-Tier IV equivalents. For LLMs that must stay in India we use Azure OpenAI India regional deployments (where the specific model is available) or self-host Llama 3, Mistral, and IndicLLM variants on GPU clusters in Indian regions or on the IndiaAI Compute Portal. Cross-border transfer is permitted under DPDPA unless the Central Government restricts a specific country in a future notification, but the contract still must satisfy the data fiduciary's own audit posture. We document residency in the model card and the data processing agreement.

Most custom AI work qualifies for the Indian Section 35(2AB) deduction (currently 100 percent of in-house R&D expenditure for eligible companies registered with DSIR for the in-house R&D approval), and DSIR-recognised R&D centres can apply the lower customs duty on imported R&D equipment. Startups recognised by DPIIT can claim three-year tax holiday under Section 80-IAC. AI projects can also pursue grants and compute subsidy under the IndiaAI Mission (Application Development Initiative, Innovation Centre, Datasets Platform, Compute Portal subsidy). State-level incentives in Karnataka, Tamil Nadu, Telangana, and Haryana (for Gurugram-based startups) can stack. We deliver time-tracked engineer logs, technical narratives, experiment histories, and failed-hypothesis documentation aligned with DSIR Form 3CK and the IndiaAI grant template. Final eligibility sits with your CA and the relevant approving authority.