AI & ML automation in Delhi & across India
AI and machine learning automation for businesses that want to reduce repetitive work: customer support assistants, automatic data extraction from documents, lead qualification, report generation, and predictive insights built into the website, CRM, and tools you already use.
Automation delivery starts with a measurable pilot, then scales with logging, guardrails, and human review where accuracy matters.
Proven models and tooling connected to your existing systems through secure APIs.
Automation is scoped around business outcomes, measured in a pilot, and engineered to be reliable in production.
Accuracy and running cost are proven on your real data before any larger build.
Automations plug into your website, CRM, and apps instead of replacing them.
Data masking, access logs, and human review keep sensitive decisions under control.
The value of AI for most businesses is not a flashy demo. It is the hours saved when support questions answer themselves, invoices and documents are read automatically, leads are qualified before a salesperson calls, and reports write their own first draft.
I integrate large language models and machine learning into the systems you already run, such as your website, CRM, and internal tools, with guardrails, logging, and human review where accuracy matters. Every automation starts with a measurable goal and a small pilot, so you can see the return before scaling it.
Website and WhatsApp assistants trained on your own content that answer customers and capture qualified leads.
Extract data from invoices, forms, resumes, and PDFs straight into your CRM or database.
Lead scoring, ticket routing, follow-ups, and report generation that run automatically across your tools.
Machine learning models for demand forecasting, churn signals, and anomaly detection on your business data.
Identify the repetitive tasks where automation saves the most time or money.
A focused proof of concept on real data, with accuracy and cost measured against clear targets.
Connect the automation to your CRM, website, or apps with logging, fallbacks, and human review.
Track quality, cost, and usage, and refine prompts and models as your data grows.
Common wins include answering customer questions, qualifying and routing leads, extracting data from documents and emails, drafting reports and replies, classifying support tickets, and forecasting demand from historical data.
Yes, when it is built properly. Sensitive fields can be masked before they reach a model, providers are chosen with appropriate data-retention terms, access is logged, and self-hosted models are an option for strict requirements.
Yes. Most automations connect to systems you already use through APIs, so there is no need to replace your website, CRM, or internal tools.
Build cost depends on the workflow and integrations, and running cost depends on usage volume. Every project starts with a small pilot that measures accuracy and monthly running cost before any larger commitment.
I work with OpenAI, Anthropic Claude, and Google Gemini APIs, open-source models, retrieval-augmented generation over your own documents, Python machine learning libraries, and automation built on Node.js backends.
Accuracy is measured during the pilot on your real data. Where mistakes are costly, the system flags low-confidence results for human review instead of acting on them automatically.
