Trustworthy AI
The system explains itself, admits uncertainty, and refuses to guess with someone else’s data.
We build software that people trust.
Start a projectFour products. One standard.
Zealo, TechSignal, DermaFusion, and Wonderithm. Flip a card to open the project.
Five ways we take on a product.
Each engagement starts with a written scope: the problem, the constraint, and what done looks like.
- AI product engineeringAI inside a product people will use. The model, the validation layer, and the interface are designed together.
- Native iOSSwift and SwiftUI products for iPhone and Apple Watch, built for response time, battery, and privacy.
- Applied machine learningPersonalization, ranking, and on-device inference, with an evaluation harness before anything reaches a user.
- Product designInterfaces that stay quiet. We prototype until the complexity is gone, then engineer what remains.
- Technical advisoryArchitecture, privacy, and a written build plan before a large commitment.
Products we built
to the standard we sell.
These are AutoClosure products, not borrowed client logos. They show how we design, validate, and ship.
iOS · Training
Zealo
An iOS training companion: plans, logging, nutrition, and a science check before a recommendation reaches the athlete.
1,300+
Organic downloads
1st
Place at CBIC 2026
82/82
Live-AI plan runs
- TechSignalA product for separating a real shift in the technology landscape from the noise around it.
- DermaFusionSkin-health software that aims for clarity without alarm, and privacy without a footnote.
- WonderithmAlgorithmic experiences that turn exploration into understanding, built to spark wonder rather than a habit loop.
Constraints, not slogans.
Six rules shape the work. They are how we decide what to build and what to refuse.
Validation before release
Recommendations are checked against evidence and real cases before a person has to trust them.
Privacy by design
Collect the minimum. Process on the device when that is possible. Never sell what is not ours.
Engineering craft
Architecture, performance, and the curve of an animation are the same job.
Native when it matters
We use the platform’s own tools when response time and battery are part of the product.
Long engagements, short promises
We write a scope before we start, and we build for the life of the product rather than the week of the demo.
How an engagement moves.
Nothing skips validation. Nothing ships because a demo looked finished.
- Research
Study the users, the constraint, and the way the idea fails before writing code.
- Design
Prototype until the complexity is gone and the remaining work is obvious.
- Build
Engineer with a clear architecture and a performance budget.
- Validate
Test AI output against evidence, and test the product against the task.
- Ship
Release with a privacy review and a way to roll back.
- Improve
Measure what people actually do, then change the product.
Founder, AutoClosure LLC
Manikanta Sirumalla
An iOS engineer who got tired of software that guesses.
Manikanta Sirumalla is the founder of AutoClosure LLC and the creator of Zealo. He is completing an M.S. in Data Science at UMBC and has more than five years of professional iOS development experience.
About AutoClosureNotes from the work.
How we think about validation, private AI, and interfaces that get out of the way.
- Why we validate every AI recommendation before it shipsA fluent answer is not a finished feature. The validation layer is the product.
- On-device intelligence and the future of private AIPrivacy is a decision about where the model runs, made before the first prompt is sent.
- Designing software that disappearsThe best interface for a hard task is the one you stop noticing.
Tell us what you need built.
A short brief is enough. We reply with a scope, not a slide deck.
Start a project