Chirag Kansara

• What AI can and cannot do today, shown on your own processes rather than generic demos.
• Mapping where time, money and errors go, and which processes AI should fix first.
• Private or cloud AI, data rules and governance: what may go into which tool, and who approves what.
• Measuring ROI: a baseline for each process before anything changes, and the targets you will report on.
• Leading adoption: champions, training plans and the habits that make AI stick after the first pilot.
• You leave with a short written AI roadmap your leadership team agrees on.

Who it's for: Owners, leadership teams and department heads.

Enquire about this training →  ·  How AI transformation works →

• HR: screening CVs, drafting job descriptions and offer letters, onboarding checklists and answers to policy questions.
• Sales and marketing: lead research, proposal and email drafts, CRM updates, content and campaign drafts, and weekly reporting.
• Finance: capturing invoice and expense data, reconciliations, month-end summaries and variance commentary.
• Manufacturing: SOPs and work instructions, quality and inspection reports, maintenance logs, and ERP data entry and reports.
• Rules for each team on what data may go into which tool, and how to check an answer before acting on it.
• Each person leaves with three working automations they built on your own systems.

Who it's for: HR, sales, marketing, finance, operations and production teams. No coding needed.

Enquire about this training →  ·  AI by department →

• When an agent is the right answer, and when a simple automation or a better process wins.
• Designing the agent: its tools, the data it may read, permissions, and where a human must approve.
• Building with Claude, the Model Context Protocol (MCP) and agent skills, connected to email, CRM, ERP and documents.
• Testing accuracy, cost and safety before go-live, then monitoring and audit logs after launch.
• The team builds one agent on a real process of yours during the training.

Who it's for: Developers, product owners and technical operations leads.

Enquire about this training →  ·  Our AI development work →

• Claude Code, GitHub Copilot and ChatGPT: what each is good at, and how to combine them.
• Giving AI the right context: clear specs, small steps, tests first.
• Reviewing AI-written code for security, performance and maintainability before it ships.
• From prototype to production: tests, version control, CI/CD and deployment.
• Team rules: secrets, licences, and what code may go into which tool.
• Separate tracks for developers and non-developers. Measured on an agreed team workflow under our 10× productivity guarantee.

Who it's for: Engineering teams, product managers, founders and business users who build internal tools.

Enquire about this training →  ·  Making AI-built apps production-ready →

• The Associate track for everyone who uses Claude: prompting, task decomposition, checking answers, model and feature choice, context.
• The Developer track for engineers: the Claude API, agents, Claude Code, hooks, context engineering, cost, guardrails and security.
• Follows the ten courses of Anthropic's Claude learning path, online, with weekend batches for groups and corporate training on-site or off-site.
• A learning portal with all course material, exam simulations and full support through exam preparation. Claude certification is available only through Claude partners; IndaPoint is one.
• Objective-by-objective review and practice questions before each person books the exam.

Who it's for: Anyone who uses Claude at work, and developers who build on it.

Enquire about this training →  ·  Full Claude certification training →