Engineering intelligence for measurable business outcomes

Production-ready AI, resilient systems, and actionable strategy — enabling startups and enterprises to ship with confidence.

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Services

We provide practical, repeatable engineering and strategy services to reduce time-to-market and operational risk.

AI & Machine Learning

End-to-end model lifecycle: data strategy, model development, validation, deployment, monitoring and retraining. Focus on reliability and explainability.

  • Data pipelines, feature stores
  • MLOps & CI for models
  • Model explainability & fairness

Software & API Engineering

Robust backend systems, microservices, and APIs built for scale with test automation and observability baked in.

  • FastAPI / Node / Go microservices
  • Secure authentication & RBAC
  • Automated testing

Cloud & Infrastructure

Architect and implement cloud infrastructure, cost-optimized deployments, container orchestration, and CI/CD frameworks.

  • Kubernetes & Docker
  • Infrastructure as code
  • Cloud cost optimization

Technical Advisory

Architecture reviews, technical due diligence, engineering hiring plans, and product roadmap consultation.

  • Architecture audits
  • Security & compliance
  • Roadmaps & resourcing

Selected Case Studies

Practical summaries of meaningful outcomes we delivered for clients.

Flood Detection (Computer Vision) — NGO

Problem

Automate detection of flood-affected regions from satellite imagery to accelerate emergency response.

Solution & Results

  • Trained U-Net segmentation pipeline with custom augmentation; built inference API and dashboard.
  • Achieved 92% IoU on held-out test set; enabled nightly batched processing for situational awareness.
  • Delivered a Dockerized stack + monitoring for 24/7 operations.

Resume Parsing & Screening — HR Tech

Problem

Reduce manual resume screening time for high-volume hiring.

Solution & Results

  • Built an NLP pipeline for entity extraction, skill matching and ranking; integrated with client ATS.
  • Reduced screening time by 60% and increased candidate quality score by 22%.

Demand Forecasting — Retail

Solution & Results

  • Developed time-series forecasting ensemble (Prophet + LSTM) with automated retraining and anomaly detection.
  • Improved inventory accuracy by ~25%, cutting stockouts and excess stock.

How we work — practical, low-risk engagement model

Discovery

30–60 minute scoping calls, data availability review, success metrics and constraints documented.

Proof of Value

Short sprint (2–4 weeks) to validate core assumptions with a prototype or POC.

Scale & Harden

Productionization: testing, CI/CD, monitoring, security and scalable infra for sustained operations.

Support & Knowledge Transfer

Documentation, training and optionally a maintenance SLA to keep systems healthy.

Leadership & Core Team

Small senior team with hands-on experience delivering production systems.

Team

Jyotirmay

Founder & Principal Engineer

Experience: ML systems, CV, production infra. Leads technical delivery and architecture.

Team

Engineering Lead

Backend & DevOps

Designs resilient backends, CI/CD and infrastructure automation.

Team

Data Scientist

ML Research & Production

Modeling, evaluation and MLOps practices for reliable deployment.

Resources & Thought Leadership

Whitepaper — Production ML Best Practices

Downloadable summary of our approach to robust ML deployment.

Blog — From Prototype to Production

Practical posts on CI/CD for models, feature stores, and observability.

Frequently asked questions

How long does a typical engagement take?

Discovery: 1–2 weeks. POC: 2–6 weeks. Production: 4–12+ weeks depending on scope.

Do you provide post-launch support?

Yes — options for hourly ad-hoc support or a monthly SLA depending on need.

Contact

Tell us about your challenge — we’ll propose a practical next step.

Email: contact@jcnconsultancy.in

Response time: Typically within 24 hours

Engagements: Remote, global

Phone: +91-63778 39757

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