Industry research (Deloitte, Tech Trends 2026) found that while 38% of organizations are piloting agentic AI, only 11% ever get it running in production. That gap — between a demo and a system your business can depend on — is exactly where MindThinkAI works. We don't stop at the pilot.
We don't outsource pieces of the stack — the same practice covers the model, the data, and the product it lives in. Examples below are representative starting points, not a claim that we've built exactly this — if one sounds like your problem, that's usually where the first conversation begins.
Real-time video and image models for behavior analysis, object detection, and automated alerting — built on YOLO, OpenCV, TensorFlow, and PyTorch.
Predictive models for pricing, ranking, and recommendation, trained on real-world, messy data and shipped straight into production apps.
Memory-enhanced chatbots and LLM advisory layers that turn raw model output into plain-language guidance people actually use.
ML-driven phishing simulation, typosquatting detection, and social-engineering monitoring, built for enterprise security teams.
Market and KPI analysis, trading-strategy research, and data visualization that turns raw numbers into decisions.
React, Next.js, and Tailwind on web; React Native on mobile — backed by FastAPI, Django, MongoDB, and SQL.
We design and build AI systems that solve a specific, named business problem — demand forecasting, document understanding, customer triage, workflow copilots — using the right mix of ML, LLMs, and autonomous agents. Every model we ship is built to be monitored, retrained, and owned, not left to drift.
4 years of focused expertise in AI/ML, data science, and agentic AI — applied directly to industry problems, not research demos.
Before we write a line of code, we design the system it lives in — one that scales, integrates with what you already run, and doesn't need to be rebuilt the day it succeeds. Two decades of enterprise architecture experience now applied specifically to AI-native systems.
18+ years architecting and designing enterprise systems, with 3+ years focused on applying AI/ML, data science, and agentic AI within that architecture.
An AI model or app is only as good as the pipeline that keeps it running. We build the CI/CD, monitoring, and operational automation that turns a working prototype into a system your team can trust in production — around the clock.
18+ years in DevOps, operations management, and application automation, including CI/CD pipeline delivery at scale.
Three projects that best represent the range of what we build — an AI-native consumer platform, a computer-vision safety product, and an enterprise security tool in live use.
An AI-powered, mobile-first platform that gives everyday buyers expert-level confidence when shopping for diamonds.
Diamond pricing is opaque and intimidating for non-expert buyers — there's no easy way to tell if a listed price is fair, or to compare options with real guidance.
In active, milestone-gated development — architecture and UX for a full AI-driven marketplace, not a single feature.
A computer-vision safety platform that watches the road so someone doesn't have to find out the hard way.
Road accidents often go unnoticed until it's too late for emergency response — and there was no automated way to assess driver behavior in real time from dashcam footage.
Live and running end to end — from raw dashcam video to an emergency alert, with no manual step in between. Covers both halves of the safety problem: ongoing behavior analysis and real-time crash response, in one shipped product.
An AI-powered training platform that teaches employees to spot real threats — by simulating the threats themselves.
Generic security-awareness training doesn't reflect what employees actually get targeted with, so it doesn't change behavior.
Actively deployed in production at aais.ai — not a pilot, a system employees are trained against today. Replaces one-size-fits-all training with simulations tuned to each employee, making the training closer to the real threat.
Two more builds that round out the range — a memory-enhanced conversational assistant and a full-stack ordering platform.
Advanced chatbots with memory and learning capabilities for AI-based customer support and NLP — retaining context across conversations for more natural, personalized interactions.
A Python + Oracle platform for browsing and ordering from multiple stores, with Matplotlib-based data visualization.
"His solution elevated our entire operation, making processes faster and more efficient. The support is also commendable, always ready to assist."
"Clients appreciate the innovative solutions, intuitive interfaces, and consistent quality brought to every project."
"With a focus on user satisfaction, the work consistently earns positive feedback and fosters long-term engagement."
We work best with teams who have a real problem to solve — not just a model to train. If that's you, let's talk.