AI & Machine Learning Services We Offer in Hyderabad
Hyderabad’s AI buyers measure vendors against Microsoft Research India, Google AI Hyderabad, and Apple ML, so generic prompt engineering is a non-starter. Our services mirror the local bar. We design retrieval pipelines on Azure OpenAI in Central India, AWS Bedrock in ap-south-2 (the Hyderabad AWS region launched in November 2022, a real differentiator for Telangana-resident workloads), and Google Vertex AI on asia-south2 for clients who need Indian data residency under DPDPA. We fine-tune open-weight models (Llama 3, Mistral, Sarvam, Krutrim) when DPDPA cross-border transfer rules or sectoral guidance from RBI rule out hosted frontier APIs. We ship classical ML on XGBoost, LightGBM, and scikit-learn for pharma, banking, and insurance problems where IRDAI and RBI examiners want explainability over headline accuracy. Every project leaves with a model card, a fairness review, and a DPDPA Article 8 data fiduciary obligations checklist.
Our AI & Machine Learning Development Process
Discovery, design, build, and deployment run on IST hours so Hyderabad product, compliance, and pharma R&D leads get synchronous standups inside HITEC City working windows rather than overnight handoffs. Discovery opens with a DPDPA 2023 classification (significant data fiduciary thresholds, cross-border transfer scope, children’s data), a sectoral overlay if RBI master directions, IRDAI information and cybersecurity guidelines, or SEBI cybersecurity and cyber resilience framework apply, and a MeitY app guideline review for consumer-facing AI. Build sprints are two weeks, each reviewed against a model card aligned with NITI Aayog’s Responsible AI principles. Deployment includes monitoring, drift detection, and a rollback runbook that a Telangana enterprise CISO or a pharma quality team can sign off without a second engagement. When research depth matters, we scope collaborations with IIIT-H CVIT, IIT-H, or ISI Hyderabad rather than pretending we invented the method internally.
AI Opportunity Assessment
1-2 WeeksWe audit your data, workflows, and business goals to identify the highest-impact AI use cases and evaluate technical feasibility.
Data Engineering & Preparation
2-4 WeeksWe clean, label, and structure your data for model training. This includes building data pipelines, feature engineering, and establishing data quality benchmarks.
Model Development & Training
4-8 WeeksOur ML engineers build, train, and fine-tune models using state-of-the-art techniques. We run experiments, optimize hyperparameters, and validate results.
Integration & Testing
2-4 WeeksWe integrate the AI model into your existing systems via APIs, build monitoring dashboards, and conduct thorough testing with real-world data.
Deployment & MLOps
1-2 WeeksProduction deployment with automated retraining pipelines, model versioning, drift detection, and performance monitoring for continuous improvement.
Technologies We Use for AI & Machine Learning
Hyderabad AI workloads almost always demand Indian data residency, and the AWS ap-south-2 region launched in Hyderabad in 2022 makes that easier than it has ever been. We default to AWS ap-south-2 (Hyderabad) for clients who want Telangana-resident infrastructure, AWS ap-south-1 (Mumbai) for general workloads, Azure Central India (Pune) for Azure-first stacks, and GCP asia-south2 (Delhi NCR) when Vertex AI is the platform of choice. For LLM layers we use Azure OpenAI Central India, AWS Bedrock with Anthropic and Cohere on ap-south-1, Sarvam and Krutrim for Indic-language workloads, and self-hosted Llama 3, Mistral, or Qwen on NVIDIA H100 instances when DPDPA cross-border rules or sectoral RBI/IRDAI guidance make hosted frontier APIs untenable. MLflow, Weights and Biases, and SageMaker handle experiment tracking, and SHAP, LIME, and Captum produce explainability artefacts that RBI, IRDAI, and SEBI examiners accept.
Other Services We Offer in Hyderabad
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