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Product engineering · AI governance · Jaipur & Bengaluru, India
We build AI products that hold up in production.
TrilokCloud combines engineering depth with delivery governance. The systems we ship keep working after the demo.
AI Product EngineeringAgentic Systems & GovernanceDelivery Risk ManagementCloud-Native DevelopmentTPM Leadership
What we build
Products and platforms built to last
We build software that the next engineering team can read, the operations team can monitor, and the business can change without starting over.
Operational software that lasts
Enterprise platforms
Internal systems and portals that connect teams, data, and workflows at scale.
Faster releases with lower risk
Cloud-native applications
Services built for elastic scale, observability, and secure deployment from day one.
Intelligent workflows that ship
AI-enabled solutions
Practical AI features embedded into products with governance and measurable value.
Products ready for what comes next
Scalable systems
Architecture and delivery patterns that support growth across users, regions, and teams.
Capabilities
Five capabilities. Each one addresses a specific failure mode.
Most AI projects fail between the demo and production. These are the capabilities that close that gap.
AI Product Engineering
We design and build AI features with production constraints in mind from day one. Most AI features fail because they were designed for the demo environment, not the real one.
Agentic Systems & Governance
We build and govern agentic AI systems. These are agents that act, decide, and chain steps without a human in the loop. Without governance, they fail silently and at scale.
Cloud-Native Development
We build services with observability, fault tolerance, and deployment pipelines from the start. Cloud systems that skip this become undebuggable in production.
TPM & Delivery Excellence
We run complex AI and product programmes with the delivery discipline of a senior TPM. Misaligned programmes do not fail at launch. They fail slowly over many sprints.
Platform Modernisation
We migrate legacy platforms to maintainable, observable systems. Platforms that are not modernised accumulate delivery risk until they block every new initiative.
How we build
AI + Cloud + Execution for better products
TrilokCloud connects AI acceleration, cloud-native engineering, and delivery excellence in one product development model.
01
AI
Accelerate intelligently
We apply AI only where there is a production problem that AI actually solves. The question we ask before any AI feature is not "can we add this" but "what breaks if this goes wrong at 2am and nobody is watching."
02
Cloud
Build to scale
We build with observability and deployment pipelines from the first sprint, not the last. Teams that skip this find out six months later when something fails in production and there is nothing in the logs to read.
03
Execution
Ship with precision
The founder has 20 years of programme management across consumer technology, mobility, and financial services. The pattern that repeats is not missed deadlines. It is scope that was never locked, dependencies that were never mapped, and risk that sat in someone's head instead of a log. We manage that from week one.
Why TrilokCloud
We know what production AI failure looks like.
That knowledge comes from research, from operating a live AI product, and from running complex programmes as a senior TPM.
AskShala
AI product in production
Active
Doctoral research
2
India offices
2023
Founded
AI governance is built in, not bolted on
We structure AI systems with oversight, fallback paths, and human review points from the start. Most teams add these after something breaks.
Senior TPM on every engagement
Delivery risk is managed at the programme level from week one. Not escalated to a TPM when things slip. Handled before they do.
We understand AI failure modes
The research has produced a working taxonomy of where production AI systems break. The same four patterns repeat across engagements. Prompt drift. Missing fallback paths. Unmonitored confidence degradation. Audit gaps that surface only during a compliance review. We build around each of them from the start.
We have shipped a real AI product
AskShala is live. It handles real user queries at Indian schools. We are not pitching AI concepts. We operate one in production.
Principal-level attention on every project
We are a small team by design. We do not win work and hand it to a junior team. The people you speak to are the people who build.
No fabricated proof
We do not pad our track record with client logos we cannot name or metrics we cannot verify. If we cannot show real proof, we say so.
I started TrilokCloud because I kept watching the same thing happen. AI projects would work in the demo, fail in production three months later, and cost teams six months of rework they had not budgeted for. Twenty years of programme management across consumer technology, mobility, and financial services means I have watched that failure repeat across different industries and different teams. An AI feature ships. It works in the demo environment. Then it starts behaving differently in production and nobody knows why, because nobody built the tooling to know why. My doctoral research started as an attempt to name that failure pattern precisely. It turned out there was already a field for it. That field is called AI TRiSM, the study of trust, risk, and security in AI systems. What we do at TrilokCloud is apply that framework to real product decisions, not academic papers. That is the problem we are built to solve, and it is not AI in general. We work specifically on AI systems that have to keep working when real users depend on them.
Mission and Vision
What we are building and why.
Mission
Most AI products are built to pass a review, not to survive contact with real users. We started TrilokCloud because the gap between those two things is where most teams lose six months and most budgets disappear.
Vision
To become India's trusted partner for production-grade AI product engineering, where every organisation ships AI systems that are reliable, auditable, and governed. Not just impressive in a demo.
Industries
Four industries. All chosen because the failure cost is real.
We work where AI systems need to be reliable, auditable, and governed. Not just impressive in a demo.
EdTech
We build AI assistants and learning products for Indian schools. AskShala is our proof point in production.
Enterprise
We run AI governance and platform programmes for organisations where delivery risk and auditability matter.
BFSI
We build AI and cloud products in regulated environments where fallback design and compliance are non-negotiable.
SaaS Platforms
We handle AI feature engineering and delivery governance for growth-stage product companies that ship fast.
Engineering culture
Built with ownership and precision
Our culture supports the kind of product work enterprise teams expect. Clear, modern, and accountable.
Precision
Before we write a line of code we write down what done means. No feature goes into a sprint without acceptance criteria the whole team agrees on. We have seen too many good engineers build the wrong thing perfectly.
Ownership
When something breaks in production, whoever built it is the first call. Not a helpdesk ticket, not an escalation chain. We make this explicit with every client before we start.
Modern engineering
We do not use a tool because it is current. Anything that requires a manual step to deploy, a manual step to test, or a manual step to monitor is on a shortlist for replacement.
Scalable thinking
We have inherited enough systems built for the demo to know what they cost two years later. The choices that feel optional at the start (data model, API contracts, deployment topology) decide whether the platform can change or only be rebuilt.
Trust & Compliance
Security and data handling
How we handle data, access, and accountability on every engagement.
Data stays with you
We do not retain, reuse, or share client data. All data processed during an engagement is owned by the client and handled under a signed NDA.
Secure by design
AI systems we build include access controls, audit logging, and human review points from day one. Security is not added after delivery.
Registered Indian entity
TrilokCloud Technologies Private Limited is incorporated in India (CIN U62090RJ2023PTC091124). Engagements are backed by a formal contract.
Insights & impact
What we have shipped. What we are learning.
We have one flagship product in production and an ongoing series on AI design patterns, covering where AI systems break and how to build them so they do not.
What we have built
AI Design Patterns. Ongoing series.
Published regularly. Each post covers one failure mode and how to design around it.
Contact
Let's Build Together
Tell us about your product. We respond within 1 business day.
Jaipur Office
3/286, Vidhyadhar Nagar, Jaipur, Rajasthan – 302039
Bengaluru Office
769, 14 Cross, J.P. Nagar Phase 1, Bengaluru 560078