Rohan Shinde · Full-Stack & AI Developer at Fristine Infotech · Pune
Profile
At Fristine Infotech, I build software for organisations that need more than a working demo: systems designed deliberately, economical to run, dependable when dependencies fail, and measurably more efficient than what they replace.
An engineering foundation and an MBA in Information Technology mean every decision is weighed against cost, risk and outcome, whether the client is a school, a clinic, a bank, a manufacturer, a retailer, an insurer or a growing small business.
On the AI side I design agents, retrieval over a client's own documents, human-approval workflows, and the evaluation and guardrails that make LLM behaviour something you can measure and trust.
What I do
- System design & architecture
- AI agents & RAG
- Full-stack delivery
- Cost & efficiency reduction
At a glance
- Role
- Full-Stack & AI Application Developer
- Working at
- Fristine Infotech
- Based in
- Pune, Maharashtra
- Home town
- Dhule, Maharashtra
- Education
- B.Tech · MBA in Information Technology
- Certified
- Claude Certified Architect – Foundations
- Industries
- Education · Healthcare · Retail · Manufacturing · Banking · Insurance · Small business
- Reach
- rohan@rohanshinde.in
Production apps led
LLM agent types in one platform
Orchestrator uptime
Less manual onboarding
What I deliver
01
Design the system
Architecture comes before code. Tenancy, data boundaries, failure modes and the cost model are settled up front, so the product grows without being rebuilt.
13 agent types on one multi-tenant platform
02
Reduce the cost
Right-sized infrastructure, automated manual work and faster releases. The goal is a lower total cost to build, run and change.
60% faster release deploys · 70% less onboarding effort
03
Build it reliable
Fallbacks, guardrails, isolation and observability, so the product keeps its promises even when a dependency does not.
99%+ orchestrator uptime · zero cross-tenant leakage
04
Improve efficiency
Repetitive, error-prone work becomes a workflow people trust, with fewer hand-offs, fewer mistakes and clearer reporting.
45% better reporting · 65% faster ticket resolution · 55% fewer scheduling errors
How I solve it
- Identify the problem: Find where time, money and errors leak. Map the workflow, read the data and name the one metric that must move.
- Apply automation & AI: Automate the repeatable. Use AI where judgement is needed. Rules and workflows for the predictable, LLM agents and RAG for language and decisions, and a human approving anything risky.
- Resolve the major issues: Take the biggest risks first. Data isolation, access control, failure modes and cost hotspots are settled before they become expensive.
- Design the system: Architecture that fits the problem, not the trend. Services, data model, integrations and a cost model agreed on paper before any build.
- Design the process: The new way of working, end to end. Roles, approvals, hand-offs and fallbacks drawn out so people know exactly what changes.
- Design the experience: Interfaces people understand without training. Role-based screens and clear flows, so adoption needs no manual.
- Develop: Small increments, shipped often. Clean APIs, role-based access, guardrails and observability built in from the first release.
- Test: Prove it works before anyone relies on it. Functional and load tests, plus LLM evaluation sets for answer quality, task completion and regressions.
- Deploy & improve: Live, watched and getting better. Containerised CI/CD releases with tracing and logging, tuned for cost and efficiency from real usage.
Identify the problem
Find where time, money and errors leak.
Map the workflow, read the data and name the one metric that must move.
- Workflow mapping
- Data review
- Target metric
Identify the problem
Find where time, money and errors leak.
Map the workflow, read the data and name the one metric that must move.
- Workflow mapping
- Data review
- Target metric
Selected work
Industries
01
Education
The problemStaff answer the same questions all day.
How I solve itRole-based portals and an assistant grounded in your own policies.
What goes wrong
Admissions, timetables, fees and records are scattered across spreadsheets and inboxes, and staff spend their days answering the same questions again and again.
What I build
- 01Role-based portals for administrators, faculty and students, so each person sees only what they need.
- 02An assistant grounded in the prospectus, policies and FAQs (RAG) that answers routine student and parent queries and hands anything unclear to a person.
- 03Automated admissions, attendance and notification workflows, with dashboards for enrolment and performance.
What changes
Fewer repetitive queries, faster administration and clear visibility for leadership, without adding headcount.
Full breakdown of education →02
Healthcare
The problemScheduling errors and paper records slow the clinic down.
How I solve itOne role-based system for bookings, records and staff.
What goes wrong
Scheduling errors, paper records and unclear responsibilities slow clinics down, while patient data demands careful access control.
What I build
- 01Role-based access for admins, doctors and receptionists, so every record is visible only to the people who should see it.
- 02Appointment booking, patient records and staff management in one system, with real-time analytics on clinic performance.
- 03A modular, service-separated backend with secure APIs and session management. Any AI is limited to administrative tasks and sits behind guardrails.
What changes
Fewer scheduling mistakes and less admin work. The same design cut scheduling errors by 55% and administrative scheduling workload by 50% in ClinicCare.
Full breakdown of healthcare →03
Retail
The problemOrders, stock and support live in separate tools.
How I solve itOne source of truth, plus a support assistant that knows your catalogue.
What goes wrong
Orders, stock and customer conversations live in separate tools. Teams reconcile by hand, stock-outs surprise them and support costs rise with every sales peak.
What I build
- 01A single order and inventory service so every channel reads the same source of truth.
- 02A support assistant grounded in the product catalogue and return policy (RAG), with a clean hand-off to a human for anything uncertain.
- 03Dashboards for demand, stock levels and support load, so decisions stop depending on spreadsheets.
What changes
Fewer stock-outs, less manual reconciliation and a support team that handles the exceptions instead of the repetition.
Full breakdown of retail →04
Manufacturing
The problemDelays surface only once they are expensive.
How I solve itLive dashboards, slippage alerts and reports that write themselves.
What goes wrong
Plans sit in spreadsheets, progress is reported late and nobody can see where people, machines or milestones are slipping until it is expensive.
What I build
- 01Workforce and project dashboards with role-based views, from shop floor lead to plant manager.
- 02Real-time sync across milestones, assignments and resource allocation, with alerts on slippage.
- 03Automated operational reports so leadership reads a dashboard instead of waiting for a document.
What changes
Earlier visibility into delays and faster, lighter reporting. The same pattern lifted reporting efficiency by 45% in WorkForce360.
Full breakdown of manufacturing →05
Banking
The problemEvery action must be auditable and every record protected.
How I solve itTenant isolation, policy-gated approvals and a full decision trace.
What goes wrong
Every workflow must be auditable, access must be tightly controlled, and onboarding is slow because too much of it is still manual.
What I build
- 01Strict tenant and role isolation: tenant-scoped JWTs plus database-level row isolation, so one client's data can never surface in another's.
- 02Policy-gated approval pipelines that keep a human in the loop for consequential actions, with guardrails on every AI output.
- 03Full traces and structured logs of prompts, tool calls and decisions, so every outcome can be explained afterwards.
What changes
Faster onboarding with a clear audit trail. The pattern cut manual onboarding effort by 70%, and a no-code page builder shortened deployment cycles by 80%.
Full breakdown of banking →06
Insurance
The problemThe answer sits in a policy clause, behind many approvals.
How I solve itDocument-grounded answers, stateful approvals and measured AI quality.
What goes wrong
Policies, forms and claims are document-heavy. Answers depend on reading the right clause, and approvals pass through many hands.
What I build
- 01Retrieval-Augmented Generation over policy and process documents, so answers are grounded in the source text rather than guessed.
- 02Stateful approval workflows (pending → dispatched → awaiting approval) with conditional routing and human checkpoints.
- 03Evaluation sets and guardrails that measure answer quality and block unsupported output before it reaches a customer.
What changes
Quicker, more consistent answers and cleaner hand-offs, with AI that stays inside policy and can be measured.
Full breakdown of insurance →07
Small business
The problemNo IT team, little budget, and the owner's day lost to admin.
How I solve itRight-sized systems that cost little to run and are easy to own.
What goes wrong
There is no IT team and little budget. Admin work eats the owner's day and heavyweight software is both too costly and too complex.
What I build
- 01Right-sized architecture on managed, pay-as-you-go cloud services, so running cost tracks real usage.
- 02Automation of the repetitive jobs (scheduling, records, reminders and simple reporting) with an interface staff pick up quickly.
- 03Clear ownership and hand-over: simple stack, documented, easy for the next developer to extend.
What changes
Lower running cost, fewer manual errors and a system the team can own, understand and extend.
Full breakdown of small business →
Capabilities
AI / LLM
- Gemini 2.0 Flash / 2.5 Pro
- LangChain
- LangGraph
- RAG
- Embeddings & Vector Search
- Tool / Function Calling
- Prompt Engineering
- Structured Outputs
- Context & Memory
Agents
- A2A Orchestration
- Multi-Agent Pipelines
- Human-in-the-Loop
- Workflow Automation
Evals & Guardrails
- LLM Evaluation
- Policy Gating
- I/O Validation
- Fallback Handling
- Tracing
- Structured Logging
Frontend
- React 18/19
- Next.js
- Redux Toolkit
- Zustand
- Vite
- Responsive Design
- Drag-and-Drop UI
Backend
- Python
- Node.js
- FastAPI
- Flask
- REST APIs
- JWT Auth
- Migrations
- Microservices
Data
- PostgreSQL + pgvector
- Supabase
- SQLite
- NoSQL DataStore
- Cloud SQL
- Multi-tenant Isolation
Cloud & DevOps
- GCP Cloud Run
- Cloud SQL
- Secret Manager
- Docker
- Compose
- CI/CD
- Railway
- Vercel
Practice
- Agile / Scrum
- RBAC
- CRM Integrations
- BI Dashboards
- Git & GitHub
- Linux
FAQ
Who is Rohan Shinde?+
Rohan Shinde is a Full-Stack & AI Application Developer based in Pune, India, working at Fristine Infotech. He designs and builds production web applications, multi-tenant SaaS platforms and LLM-powered business tools, with a focus on lower cost, reliability and efficiency.
Which industries does Rohan work in?+
Education, healthcare, retail, manufacturing, banking and insurance, as well as small businesses. The work centres on workflow automation, document-grounded AI assistants, role-based dashboards and tenant-isolated SaaS.
Where is Rohan based?+
Rohan is based in Pune, Maharashtra, India. His home town is Dhule, Maharashtra.
How does Rohan approach projects in different industries?+
Every engagement follows nine stages: identify the problem, apply automation and AI, resolve the major issues, design the system, the process and the experience, then develop, test, and deploy and improve. Each stage is shown on the website as an animated walkthrough. The solution is tailored to the industry: student and admin portals for education, role-based clinic systems for healthcare, inventory and support automation for retail, workforce dashboards for manufacturing, audited and tenant-isolated workflows for banking, document-grounded assistants for insurance, and lean low-cost systems for small businesses.
What does Rohan specialise in?+
System design, LLM agents with tool/function calling, Retrieval-Augmented Generation (RAG) on pgvector, LangChain and LangGraph workflows, multi-agent orchestration, and LLM evaluation, guardrails and observability, on top of React/Next.js frontends and FastAPI, Flask and Node.js backends.
Is Rohan Shinde Claude certified?+
Yes. Rohan holds the Claude Certified Architect – Foundations certification, covering AI architecture best practices for reliable LLM systems.
What has Rohan built?+
A multi-tenant SaaS platform with 13 LLM agent types (SalesPulse AI), an AI corporate travel system on GCP Cloud Run (JourneySync), a workforce dashboard (WorkForce360) and a dental clinic management system (ClinicCare), among 6+ production applications.
What is Rohan's educational background?+
A B.Tech from SVKM's NMIMS Global University and an MBA in Information Technology from Dr. D. Y. Patil Vidyapeeth.
How can I contact Rohan?+
Email rohan@rohanshinde.in, use the contact form at /contact, or message him on LinkedIn at linkedin.com/in/rohanshinde0407. He is based in Pune, Maharashtra, India.