Capabilities & build library
This is a transparent library of 77 scoped briefs across 18 engineering domains—not a gallery of invented client logos or completed-project claims.
Representative briefs
Each card below is an existing build brief: a concrete starting point that can be adapted to a student capstone or a company problem. It is not presented as completed client work.
JavaScript Full-Stack
An org-and-workspace platform where the tenant filter is enforced by the data layer rather than by remembering it — and the hard part is keeping it enforced inside a background job, where there is no request, no session, and no context to read it from.
Mobile Apps
Two-sided app with live tracking, in-app payments, ratings, and a provider dispatch algorithm.
AI & LLM Applications
Planner, researcher, and critic agents that decompose a question, search, and adversarially verify each other before answering.
Data Engineering
A full medallion architecture — raw, cleaned, and business layers — with orchestration, cataloguing, and cost controls.
Cloud & DevOps
Metrics, logs, and traces unified, with alerts tuned so they mean something and an on-call runbook behind each one.
Robotics, Drones & Autonomous Systems
A rover that maps an unseen floor, then runs a waypoint mission through it while avoiding people who step into its path — with rosbags, a defensible TF tree, and map artefacts that survive a viva.
Engineering coverage
Explore the tools, company use cases, and project briefs already documented for every domain.
Internal tools, admin portals, REST and GraphQL APIs, dashboards, and Python services that need to be maintainable after we leave.
Spring Boot microservices, REST APIs, legacy modernisation, JVM performance work, and integration with existing enterprise systems.
RAG over your own documents, support copilots, document extraction pipelines, agentic workflows, and evaluation harnesses so you can measure quality instead of guessing.
Churn and risk scoring, recommendation, anomaly detection, and taking an existing notebook to a served, monitored model — the model itself; the decision it feeds and the experiment that judges it sit with Data Analytics & BI.
Computer vision for inspection and quality control, OCR and document understanding, audio models, and fine-tuning open-weight models on your own data.
ETL and ELT pipelines, streaming ingestion, orchestration and freshness guarantees, physical warehouse loading, and rescuing pipelines that break every week — this is the layer that gets the data there on time and uncorrupted; what the numbers mean once it lands belongs to Data Analytics & BI.
Cross-platform product apps, internal field apps, store releases, and taking an existing app through review and launch.
Cloud migration, Kubernetes, CI/CD, cost optimisation, observability, and incident-response readiness.
Secure code review, threat modelling, authentication and authorisation design, dependency and supply-chain audits, and security hardening before an audit.
Telemetry pipelines, device fleet management, industrial monitoring, and edge inference where the cloud round-trip is too slow.
Product MVPs, Next.js web apps, Node and Express APIs, realtime features, Stripe or Razorpay payment integration, and taking a JavaScript prototype and making it something a team can still maintain a year later.
RTL design and verification support: cocotb and UVM-style testbenches taken to coverage closure, FPGA prototyping, and blocks pushed through synthesis to timing, area and power sign-off on an open PDK.
Converter and inverter design, motor-control firmware, battery management and state-of-charge estimation, drive-cycle and range modelling, and grid-tie compliance and power-quality work.
PHY-layer simulation, SDR receiver chains, classical image-processing pipelines, and reproducing a published algorithm as code that actually runs.
ROS 2 integration and Nav2 tuning, manipulator kinematics, PX4/MAVLink mission and ground-station software, simulation rigs that regression-test autonomy before it meets a real floor, and edge perception on Jetson-class hardware using a permissively licensed detector (RT-DETR) where Ultralytics YOLO's AGPL-3.0 terms do not fit a commercial build.
Semantic and dimensional modelling in dbt, metric definitions that stop two dashboards disagreeing about revenue, BI builds and migrations in Power BI or Tableau, and classical forecasting, experiment design and readouts — the layer above ingestion, where a number has to resolve to one meaning.
Test strategy and automation frameworks, turning a manual regression pass into a CI gate, stabilising suites the team has learned to ignore, API and contract coverage, load tests with thresholds that fail the build, and regression gates for LLM features someone else has already built.
Protocol evaluation and capacity what-ifs before anything touches production hardware, SDN controller applications, V2X and vehicular network modelling, and turning an internal performance claim into a measurement someone else can reproduce.
Bring us a product brief, a business problem, or a final-year project. We’ll turn it into a clear scope, a working build, and a handover you fully own.
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