OUR TEAM
One team runs the whole loop. Not four teams handing it off.
Data, cloud, product, and AI usually sit in four separate teams, each shipping its own slice and handing off to the next. Control Loop keeps them in one team instead, because the failure almost never lives inside a layer. It lives in the seam between two of them. Below is that team, not a hiring pitch.
HOW WE'RE ORGANIZED
Six practices, held together on purpose.
Each practice below is organized around one of the firm's service lines, and none of them ships in isolation. The same team carries a decision from the data underneath it through to the agent that reads it.
Data Engineering
Owns pipelines and warehouses built so every downstream decision can be trusted. The practice's bar is what a platform does at 3 a.m. unattended, not what it does in a demo.
Cloud Architecture
Owns infrastructure that scales ahead of demand and stays invisible when it's working. A quiet on-call rotation is the practice's actual scoreboard.
Product Development
Owns the loop of shipping a first version early and refining it against real usage. Progress is measured in decisions users made with the product, not story points closed.
Applied AI
Owns the practice where models and agents get placed exactly where their judgment compounds. More prototypes get killed here than shipped, and that ratio is treated as healthy.
RPA Expertise
Owns automation built directly into the operational processes that run a client's business. A good rollout is judged by how quickly people forget the process was ever manual.
Enterprise SaaS Engines
Owns the platforms other software gets built on top of: multi-tenant and supported like a product, because it is one.
Full detail on each practice's work lives on the services pages.
ONE TEAM
Most systems don't fail in a layer. They fail in the seam between two of them.
Data, cloud, product, and AI are usually four separate teams, often at four separate vendors, each optimized for its own slice and handing the next one a spec instead of a conversation. The handoff is where a requirement goes stale, a security assumption goes unchecked, and a model trained on last quarter's data keeps running unattended.
Control Loop runs all four as one team instead. The people who design a pipeline can see how an agent will read it. The people who own the cloud bill can see what a product decision will cost to run once it ships. That's the real argument for the roster below: not that everyone on it is senior, though they are, but that between them they cover the whole loop.
- Data engineering decides what's true. If that team never talks to the people building the product, the product ships confident and wrong.
- Cloud architecture decides what's affordable and what's safe. If that team never talks to the people training a model, the model gets expensive or exposed after launch, not before it.
- Product and AI decide what a user, or an agent, actually does next. If that team never talks to the people who own the data and the infrastructure, the roadmap promises things the platform can't hold.
THE ROSTER
The people who run the loop.
Nobody below is a placeholder, and there's no generated avatar standing in for someone who hasn't signed off. Five real people, mapped to the practices they actually run.
LEADERSHIP
Nagaraj
Chairman
Nagaraj chairs Control Loop after more than 30 years in operations, account, and program management, running engagements bigger than most single product teams ever see: insurance portfolios, tax and financial platforms, aviation programs, HR systems, and complex B2B accounts, staffed by teams spread across Europe, the US, Canada, and Asia.
The pattern held across every one of those programs. The risk was rarely the code itself. It was the seam: a vendor team that had never spoken to the client's own engineers, a QA function bolted on after the architecture was already frozen, a rollout with nobody senior enough in the room to own its whole shape. That is the exact failure mode now swallowing large AI and cloud programs: a model that behaves correctly in a demo and drifts once it hits production, because nobody built governance around it. Coordinating that, keeping distributed teams pointed at one outcome across time zones, is what Nagaraj has done for three decades and now does across Control Loop's practices.
He holds a Six Sigma Green Belt, is a PMI member, and has run delivery under PRINCE2, ISO, and CMMI process models. None of that replaces judgment. It's the discipline behind it, and the reason business owners hand him the cross-team messes nobody else wants to untangle.
Anurag
Head of Engineering
Anurag sets technical direction across all seven of Control Loop's practices: data engineering, cloud architecture, product development, agentic AI, RPA, ML models, and the SaaS engines client platforms get built on. He is the one who signs off on an architecture before it reaches a client's production environment, and still expects to read the pull request himself.
His bar for a system is easy to state and hard to hit: it has to survive the day Control Loop leaves. That means code a client's own engineers can maintain without a translator standing next to them, decisions written down well enough to survive a handover, and a standard that doesn't soften once the interesting part of the problem is solved. He stays hands-on because judgment about a codebase fades fast the moment someone stops writing in it.
SENIOR ENGINEERING
Prateek
Senior Engineer, Data Platforms
Prateek owns Control Loop's data platform work: the pipelines and warehouses every downstream decision in an engagement depends on, whether that decision is a dashboard, a forecast, or an agent reading straight off the data underneath it.
Durga
Senior Engineer, Cloud Architecture
Infrastructure decisions run through Durga: the security posture a client inherits, the cost curve an engagement gets built on, and the on-call reality once a system is actually live. He is Control Loop's senior engineer for cloud architecture.
Keertana
Senior Engineer, AI Systems
Every agent Control Loop ships has to answer one question first: is its autonomy actually bounded? Keertana owns that question as the firm's senior engineer for AI systems, from scoping an agent down to a job it can finish, through evaluation, through the guardrails that keep it inside its lines.
GET IN TOUCH
Every engagement starts with a real conversation.
Start the conversationhello@controlloop.tech