---
title: "Case Studies | Manas Nikam, Forward Deployed Engineer"
canonical: https://manasnikam.dev/case-studies/
updated: 2026-09-23
---


# Case studies

I'm Manas Nikam. What the client needed, what I built, what changed, and what I would do differently. Client work first, then hackathon builds, each labelled; the first one took a supplier booking from about 10 minutes to about 30 seconds.

## Client work

- [Integrating VIA Rail and JonView into a tour operator's booking system](https://manasnikam.dev/case-studies/via-rail-jonview-supplier-integration/) (May 2023 to present (ongoing)): Three travel suppliers wired into a live itinerary system for Fresh Tracks Canada: JonView search and booking with a circuit breaker and state sync, VIA Rail built end to end in five dated steps, a Rocky Mountaineer scraper. Per-product booking time went from about 10 minutes to about 30 seconds. Stack: Python, Django, Django REST Framework, PostgreSQL, Redis, WebSockets, AWS ECS, GitHub Actions, Salesforce, SonarQube.
- [Gemini invoice OCR and automated Tally invoicing for a printer-fleet business](https://manasnikam.dev/case-studies/cd-infoware-gemini-ocr-tally-invoicing/) (May to September 2026 (ongoing)): Live for CD Infoware, an Indian printer-services company: invoice OCR on Gemini through Vertex AI with a 10-instance cap and per-invoice cost in USD and INR, plus a nightly Konica Minolta meter scrape that drafts one Tally-format GST invoice per device per month. 111 commits, all mine. Stack: TypeScript, React 19, Vite, Tailwind, React Native, Firebase, Vertex AI, Gemini, Puppeteer, Playwright, pnpm, Turborepo.
- [Monitoring a Postgres fleet with Lambda, DynamoDB, and one secret](https://manasnikam.dev/case-studies/postgres-fleet-monitoring/) (July to September 2026): Spec approved on 23 July 2026, then built and documented alone inside Fresh Tracks Canada's AWS account: EventBridge every 30 minutes, a collector Lambda in private subnets, DynamoDB with a 90-day TTL, a dashboard behind an internal ALB, 11 metrics with thresholds, and a least-privilege pg_monitor role. Adding a server is a secret edit, not a deploy. Stack: Python, PostgreSQL, AWS Lambda, Amazon EventBridge, Amazon DynamoDB, Application Load Balancer, AWS Secrets Manager, GitHub Actions.

## Hackathon builds

- [AgentReady: scoring whether the web is ready for agents](https://manasnikam.dev/case-studies/agentready-webmcp-benchmark/) (3 to 10 September 2026): A benchmark that scores sites 0 to 100 on whether AI agents can complete tasks through the raw UI versus WebMCP tools: 13 WebMCP tools, serverless audits on Cloudflare (Queues, Browser Rendering, Workers AI, D1), an eval runner with N runs per site, 95% confidence intervals and an 8-category failure taxonomy. Built and submitted; outcome not recorded. Stack: TypeScript, Cloudflare Workers, vinext, D1, Workers AI, Browser Rendering, Cloudflare Queues, Playwright, WebMCP.
- [Three agents on Cloud Run in three days, two integrated with vendor MCP servers](https://manasnikam.dev/case-studies/adk-agents-mcp-cloud-run/) (8 to 10 September 2026): 3 production agents on Cloud Run in 3 days, 2 integrated with vendor MCP servers (ClickHouse, Grafana): a screenplay clearance pipeline, a retention analyst over mcp-clickhouse, and a VFX war-room agent over mcp-grafana that writes back annotations and incidents. Each live with a demo video. Built and submitted; outcome not recorded. Stack: Python, Google ADK, Gemini 2.5, Vertex AI, FastAPI, Cloud Run, MCP, ClickHouse, Grafana, Prometheus, Loki, OpenTelemetry.

Hackathon builds are where I test new tooling on a deadline; client builds are where it earns its keep; both are on this site, labelled, and I do not claim a placement I do not have.