Build with AI — Software Product & Delivery Consulting
Consulting for founders and enterprise teams who want to ship AI-assisted software without burning quarters. I help scope the product, choose the stack and tooling, set delivery rhythm, and keep quality high while using AI to move faster.
- Product scoping, roadmap and delivery planning.
- AI tooling stack: Cursor, Claude Code, GitHub Copilot, CodeRabbit, Lovable.
- Architecture reviews and enterprise readiness checks.
- Hands-on pairing with your engineers, not slide decks.
Build with AI in one paragraph
Build with AI is product and delivery consulting for teams shipping AI-powered software. Praveen Jha scopes the MVP, designs the AI architecture (LLMs, RAG, agents), sets up Cursor, Claude Code and Lovable workflows, and links the product to pricing and sales. Engagements start with a one-week discovery sprint from $2,500.
Who it's for
- Non-technical founders: You have customers and a problem worth solving, but no engineering team yet. You need a clear MVP scope, a sensible stack and a delivery partner you can trust.
- CTOs with small teams: Your engineers are good but stretched. You want AI coding workflows that genuinely speed delivery up, and an outside view on architecture and model choices.
- Enterprises piloting AI: You have use cases and budget but pilots stall before production. You need governance, evaluation and an architecture that survives security review.
- Agencies and operators: You build software for clients or run operations that need internal tools. You want to ship faster with Lovable, Cursor and Claude Code without losing quality.
What I help you build
MVP scoping and product strategy
Turn an idea into a buildable product with a clear first version and a path to paying customers.
- Problem, user and competitor review
- MVP scope: must-have features, what to leave out, success metrics
- 90-day roadmap with milestones you can hold a team to
- Build-vs-buy decisions for every major component
AI architecture and model selection
Design the AI part of the product so it is accurate, affordable and safe in production, not just in a demo.
- Model and vendor choice: OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Oracle OCI Generative AI
- Retrieval (RAG) design over your documents and data
- Agent and workflow design with human approval where it matters
- Evaluation plan, cost estimates and failure handling
AI-assisted delivery (vibe coding done properly)
Set up the tools and habits that let a small team ship like a much larger one.
- Cursor, Claude Code, GitHub Copilot, CodeRabbit and Lovable workflows
- Project rules, code review and testing practices for AI-written code
- Prototype-to-production path: from Lovable to a maintainable codebase
- Hands-on enablement sessions for your engineers
Enterprise readiness
Get the product through the questions enterprise buyers ask before they sign.
- Security and data-handling review for AI features
- Multi-tenant design, roles and audit trails
- Deployment, monitoring and uptime practices
- Answers ready for security questionnaires and procurement
Product-to-revenue bridge
Make sure what you build can be sold. This is where 14+ years of enterprise sales comes in.
- Ideal customer profile and positioning for AI buyers
- Pricing and packaging options
- Design-partner programme and first enterprise pilots
- Sales narrative, demo flow and outbound sequences
How an engagement works
- Discovery: We start with the business goal, the users and the constraints: budget, timeline, data and compliance. You get a written brief either way.
- Scope and architecture: A focused MVP scope, the stack and AI design, risks and how we will test them, and a 90-day roadmap.
- Build: I build alongside your team, or for you if you don't have one yet, in short cycles with demos you can see and click, using Claude Code, Cursor and Lovable.
- Harden: Security, evaluation of AI outputs, performance, deployment and monitoring, so the product holds up with real users and real data.
- Launch and grow: Pricing, positioning, design partners and the first sales conversations, then iterate on what customers actually use.
Ways to work together
| Engagement | Price | Length | Best for |
|---|---|---|---|
| Discovery sprint | from $2,500 | 1 week | Deciding what to build and how, before you commit a budget. |
| Build advisory | from $6,000 | Per month | Teams that are building and want senior guidance every week. |
| Fractional product partner | from $12,000 | Per month, ongoing | Companies that need product leadership embedded in the team. |
AI products delivered
- Stock Assist AI — Agentic AI Financial Analysis SaaS (Fintech): Paying users 46 (at peak); Uptime 99.8%
- ClearVoice — AI Voice Agent for Financial Services Support (Financial Services): Call deflection 58%; Handle time 87s (average)
- Azimuth — AI Project Estimation & Proposal SaaS (SaaS & Agency Tools): Time saved 4–8 hrs (per proposal); Documents 3 (prd, trd and proposal)
- CareFlow AI — Human-in-the-Loop Clinic Operating System (Healthcare): Autonomous actions Zero (design target); Regions 6 (designed for)
- Fleet Sync Pro — Multi-Tenant Fleet Operations SaaS (Logistics & Fleet Management): Fuel cost 8–15% (reported reduction); Downtime 40%+ (reported reduction)
Delivered by Ortem Technologies while Praveen led sales and business development; figures as published in each case study.
Tools and platforms
- AI models and platforms: OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Oracle OCI Generative AI, OpenRouter
- AI coding tools: Cursor, Claude Code, GitHub Copilot, CodeRabbit, Lovable
- Application stack: React, TypeScript, Node.js, Python, Supabase, PostgreSQL, Vercel
Book a free call: calendly.com/pravinjha/30min · WhatsApp +91 96245 85067 · Contact form
FAQ
What does an AI product consultant do?
An AI product consultant helps you decide what to build, how the AI parts should work and how to ship them safely. That covers MVP scope, model and vendor choice, retrieval and agent design, evaluation, cost and the delivery workflow, plus how the product will be priced and sold.
How much does it cost to work with Praveen on an AI product?
A one-week discovery sprint starts from $2,500. Ongoing build advisory starts from $6,000 a month, and a fractional product partner engagement from $12,000 a month. Pricing is in USD, with INR, GBP, EUR and AED available on request.
Do you build the software or only advise?
Yes, both. Praveen builds the software himself with Claude Code, Cursor and Lovable, alongside your team or on his own if you don't have one yet, from the first prototype to production. He also leads the product and architecture decisions along the way.
Which AI models and platforms do you work with?
OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock and Oracle OCI Generative AI, chosen per use case on accuracy, cost, data residency and the platform your company already uses. Praveen is an Oracle Certified Generative AI Professional and AWS Certified Solutions Architect.
Should I build with Lovable or custom code?
Lovable is excellent for getting a working first version in front of users quickly. Custom code with Cursor or Claude Code makes sense once the product needs complex logic, integrations or scale. A common path is to prototype in Lovable, validate with users, then continue in a maintainable codebase.
Can you work with a non-technical founder?
Yes. Discovery turns your idea into a plain-English scope, the stack and delivery plan are explained in business terms, and you see working software at every step rather than technical reports.
Can my team learn to build with AI themselves?
Yes. Build advisory includes setting up Cursor, Claude Code and Lovable workflows for your engineers. For individuals, the private Vibe Coding Mastery track teaches you to build and ship your own application.
How long does an AI MVP take?
It depends on scope, integrations and data. The discovery sprint ends with a scoped MVP and a 90-day roadmap, so you know the timeline and budget before the build starts.