AI, Data & Automation
Agents, GenAI, automation and data platforms
Software & Product
Custom platforms, web & mobile, modernisation
Cloud, Security & Reliability
Managed cloud, DevOps, cybersecurity and QA
E-commerce & Apps
Commerce platforms and on-demand apps
Digital Marketing
Search, AI visibility, paid media and lifecycle
Hire & Engagement
Dedicated engineers, teams and engagement models
Technologies
Languages, frameworks, mobile and cloud platforms
Mindrops builds the pipelines, evaluation, deployment and monitoring that take LLM and ML prototypes into production, with versioned releases, quality gates and cost tracking.
Clients
A selection of the software Mindrops has designed and engineered for clients.
AI · ML
Mindrops built four production ML products in Python: predictive maintenance, computer-vision body measurement, multi-channel attribution and deep-learning manpower forecasting.
25% lower maintenance cost, 20% fewer sales returns, 15% more sales and 90% better forecasting accuracy for the respective clients.
AI · Food & Beverage
An embeddable AI chat assistant grounded in live catalogue and store data, with an “Order Now” action on every product and a no-code admin console for content and pricing.
Live across 50+ outlets in India, handling about 10,000 conversations a month and around 50 orders a day.
Government · GovTech
An AI-automated platform on Mindrops’ LazyMonkey foundation that categorises, prioritises, routes and auto-responds to every grievance, with one SLA-tracked record for central and regional teams.
Awarded via GeM (Nov 2025), it auto-triages thousands of grievances a day for a network of 1.5 lakh+ post offices.
Mindrops builds and runs the LLMOps and MLOps lifecycle that takes machine-learning and large-language-model systems to production reliably — data and training pipelines, evaluation, deployment, monitoring and cost control. The result keeps AI accurate, observable and economical once it is live.
Reproducible data, training and inference pipelines with versioning and CI/CD for models and prompts.
Automated evals, regression tests and quality gates so every change ships with test results.
Scalable, low-latency model serving — managed APIs, self-hosted or hybrid to meet data-residency needs.
Production monitoring for quality, latency, drift and hallucination, with alerting and tracing.
Token, caching and routing strategies that keep AI fast and economical at scale.
Access control, secrets, audit and guardrails wired into the pipeline from day one.
A model or LLM app works in a notebook but has no pipeline, tests or monitoring. We build the path to a dependable release.
Token spend grows faster than usage. Routing, caching and model selection bring cost back under control without losing quality.
Models are retrained and released manually, and nobody is sure which version is live. Versioned pipelines and CI/CD fix that.
Forecasts and classifiers quietly lose accuracy as data changes. Drift monitoring and scheduled retraining catch it early.
Extra capacity for software and cloud
A Mindrops team working alongside the client’s own engineers on software development and cloud-based projects, brought in to add reliable delivery capacity.
From the client’s review
“Mindrops handled complex requirements with ease and added value throughout the project.”
AI vehicle monitoring
Computer vision at a mine gate records number plates, vehicle movements and trip counts for daily reporting.
From the client’s review
“Daily reports are ready on their own, so nobody has to sit and prepare them at the end of the shift.”
AI invoice extraction
Vendor invoices are read and extracted automatically, stored, and passed to the accounting tools the finance team already uses.
From the client’s review
“The AI extraction they built works reliably with different invoice formats which was the main thing we needed.”
Warehouse operations platform
A field app and web admin panel connecting material records, site expenses and reporting across warehouse locations.
From the client’s review
“Reporting that used to take a full day of compiling sheets is now a filtered download from the admin panel.”
Recruitment & candidate management
A recruitment platform with candidate registration, applications, admit cards and a central admin dashboard.
From the client’s review
“They designed it to handle high concurrent traffic during active recruitment drives, which was critical for us.”
Fintech lending platform
A customer app, vendor app and admin panel from one team, with KYC, CIBIL credit checks and automated loan approvals.
From the client’s review
“Fintech projects have a lot of layers and it was good to work with a team that understood the credit and lending side of things.”
We review how data, models and prompts move from experiment to production today, and where that path breaks.
Data, training and inference pipelines are versioned and automated, with evals as quality gates on every change.
Models are served managed, self-hosted or hybrid to meet latency, cost and data-residency requirements.
Quality, drift, latency and spend are monitored with alerts, and retraining or prompt updates pass through the same gates.
Tell us what is in production, or stuck before it. We’ll map the gaps in your pipelines, evals and monitoring, and reply within one business day.
An engineer will respond within one business day.
Have a defined scope? Get a quote
