Fordel StudiosA studio built around one principle: the engineer who scopes it builds it.
I have been building production software for 16+ years — across insurance, healthcare, legal, and finance. I have worked on systems that process real claims, handle real patient data, and sit inside real compliance workflows. The kind of work where getting it wrong has actual consequences.
I started Fordel because I kept watching founders and product teams get burned by the same pattern: a senior engineer makes the sale, juniors do the work, and the client finds out six weeks into a project that they were never actually talking to the person who would build it.
Fordel is an AI products studio. I architect AI agents for insurance, legal, healthcare, and finance — the agent itself, the prompts, the state machine, the human-in-the-loop checkpoints — and I build the web, mobile, and backend layer it ships inside. AI tooling handles parallel workstreams; every output reviewed by me. You get senior execution at double the pace.
Abhishek Sharma
16+ years shipping production software across insurance, healthcare, legal, and finance. BTech + Masters in Computer Engineering. Full-stack: Go, Node.js, React, Next.js, Flutter. I architect, code, and stay accountable after launch. Based in India (IST), serving clients globally.
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Pabitra Sharma
Provides the financial foundation that lets Fordel take on ambitious projects and invest in long-term capability building. Keeps the studio independent — no VC pressure, no growth-at-all-costs mandate.
Satarupa Mandal
Owns the quality bar across every engagement — from test strategy through production monitoring. Every deliverable goes through her before it goes to a client.
You talk to the engineer who builds it
There is no account manager between you and the person writing your code. The engineer who scopes your project is the one who ships it. This is not a common arrangement. It should be.
Working software every week
You see real progress in real time — not a big reveal at the end of a sprint. Every week there is something you can actually use, test, or give feedback on.
Scope changes flagged before work starts
If something is harder than estimated, you hear about it immediately — not after it has already cost you two extra weeks. Surprises are a failure of communication, not of scope.
30 days post-launch accountability
Your launch is the beginning of our accountability, not the end. We monitor, fix, and iterate through the instability that always comes after go-live.
Client names are protected by NDA. The work is real.
AI agents for claims processing, underwriting, fraud detection, and compliance workflow automation. Built on top of the policy management and payment systems that mid-size insurers actually run.
AI agents for contract analysis, litigation research, eDiscovery, and intake triage. Integrated into matter management workflows; jurisdictional accuracy and audit trails preserved.
AI agents for patient intake, clinical documentation, prior authorization, and patient engagement. HIPAA-aware document pipelines, EHR integration, no PHI in model training data.
AI agents for KYC/AML, fraud detection, document processing, and regulatory reporting. Payment integrations, audit trail systems, regulator-flexible across jurisdictions.
AI agents for content distribution, multi-platform scheduling, campaign performance analysis, and approval workflow automation. Built on top of the platforms agencies and brands already use.
AI agents for itinerary management, supplier coordination, and traveler notifications. Plus the booking and reconciliation systems they integrate with.
All clients protected by NDA. Problems, approach, and outcomes are real.
AI claims intake agent for a mid-size insurer
Adjusters spent the majority of their time on data entry — manually pulling information from emails, PDFs, and spreadsheets before they could start actual claims work.
An AI agent that parses incoming documents on arrival, extracts structured claim data, triages by type and complexity, and routes to the right adjuster. Standard claims resolved without human touch. Edge cases escalated with full context attached. The agent runs against the existing claims system; we built the integration layer.
Adjusters stopped doing data entry and started doing claims work. Processing time dropped from days to hours on standard cases.
HIPAA-compliant patient record retrieval agent across 6 facilities
A regional healthcare network handled record requests manually — staff at each facility pulled, copied, and routed records independently, with no audit trail and no consistent turnaround.
An AI agent that handles request intake, identifies the right records across facilities, retrieves through EHR APIs, and assembles the response with full audit logging on every movement. HIPAA-compliant pipeline. Built alongside the existing systems, not replacing them.
Most requests fulfilled same day. Full compliance trail on every record movement. Staff freed from coordination work.
AI contract analysis agent for a litigation firm
Associates spent hours per contract identifying standard clauses, flagging jurisdiction-specific risks, and preparing summary sheets before partners could review — a bottleneck before every client negotiation.
An AI agent that surfaces non-standard clauses, flags risk by jurisdiction, and generates one-page summaries for partner review. Integrated into the existing document management workflow. Citation-aware, every recommendation traceable to a source.
Associates review a contract summary in minutes instead of hours. Partners walk into negotiations better prepared, with fewer surprises.
AI payment reconciliation agent across 4 payment rails
A fintech did month-end reconciliation manually — three people working for days to match transactions across four payment systems, with errors only visible after the fact.
An AI agent that matches transactions across rails, flags exceptions in real time, and exports audit-ready reports. Handles volume spikes without manual intervention. Confidence-scored — high-confidence matches auto-clear, edge cases get human review.
Month-end close went from multiple person-days to a few hours. Exceptions visible in real time, not discovered at close.
AI content distribution agent for a multi-client agency
An agency managing 12 clients across 6 platforms had account managers spending hours each day on manual scheduling, reformatting content per platform, and cross-posting — time that couldn't scale.
An AI agent with platform-specific adapters that ingests content once, reformats per platform constraints, and publishes through approval workflows. Client-facing performance dashboards aggregate across rails.
Account managers stopped doing manual cross-posting. Client reporting automated. Capacity freed for higher-value work.
AI itinerary management agent for a custom tour operator
A boutique tour operator built 300+ custom itineraries per season — each one a manual PDF, each rebooking a phone call, each traveler notification a separate email.
An AI agent with a template engine, supplier API integrations, and automated traveler notifications on changes. Coordinators configure; the agent executes. Notifications go out automatically when supplier schedules shift.
Itinerary creation time halved. Rebooking notifications automated. Coordinators focused on experience, not logistics.
How to Think Like a Senior Engineer
A 3-hour, hands-on workshop in Siliguri for developers who want to close the gap between writing code and thinking like a senior engineer.
Small group. Your own project. Not a toy example.
See upcoming workshops →We take on a small number of projects each quarter.
If you have something worth building, let's talk. No sales pitch, no discovery deck — just a direct conversation about what you need.
Start a ConversationFree 30-minute scoping call. No obligation.