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SezAI TechnologyAI · Product · Engineering

We put AIinto production.

We are a product studio that builds and operates its own software. From Türkiye, we run six products grounded in computer vision, natural language processing, and cloud infrastructure.

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Active products
6
Founding team
5
Founded
08·2025
Based in
Türkiye
  • Türkiye
  • AI Research
  • Product Studio
  • Cloud Infrastructure
  • TeknoNext
  • KozmosDB
  • Piyyuu
  • CepteKampüs
  • Erezervem
  • HelmetAI
Company

We don't build software for clients.We build the products we believe should exist.

SezAI is not an agency. We form the idea, do the engineering, and stay on to operate what we ship. That changes the unit of success: a feature isn't done on a delivery date, it's done when someone relies on it.

All six products pass through the same engineering discipline — a type-safe codebase, a cloud-native architecture, and a measurable path from prototype to production.

  • Vision

    To create lasting value as a technology studio that puts AI into production, scales from Türkiye, and operates the products it builds.

  • Mission

    Build, operate, and grow products across computer vision, natural language processing, and cloud infrastructure — driven by real user need, not a brief.

  • 01

    Product ownership

    Every roadmap is ours to set. Decisions come from how the product is actually used, not from a brief.

  • 02

    R&D discipline

    We run active research across AI, computer vision, and embedded systems.

  • 03

    Scalable infrastructure

    A modular, elastic foundation on Google Cloud — the same architecture from a single campus to multi-branch operations.

Products

What we build and operate

Six products, six distinct problem spaces. Each one carries a live operation — visit a product's own site for current detail.

Product index6
Production

Not an agency menu. A production discipline.

The capabilities we use to build and run our own products. The same bar applies to partnership and integration work — we don't sell brand registration, social media packages, or template websites.

  1. 01

    Putting AI into production

    From model demo to live product

    We place computer vision, NLP, and machine learning into the product's decision path — not left as a prototype. Metrics, rollback, and observability come with the first ship.

    Talk about this discipline
  2. 02

    Product systems

    From idea to operated software

    Roadmap, type-safe codebase, and operations in one hand. All six of our products passed through this discipline; partnerships run to the same engineering standard.

    Talk about this discipline
  3. 03

    Cloud-native infrastructure

    A foundation that scales

    Containers, caching, relational data, and CI/CD on Google Cloud. The same architecture carries a single campus and multi-branch operations.

    Talk about this discipline
  4. 04

    Perception and edge intelligence

    Embedded and on-device

    Perception that runs where the camera and sensors are. Latency and connectivity are real product constraints — the model is placed accordingly.

    Talk about this discipline
  5. 05

    Language and data layer

    From text to query, data to decision

    Natural-language interfaces, query generation, and data infrastructure. As on the KozmosDB line: the user shouldn't have to write SQL for the system to ask the right question.

    Talk about this discipline
  6. 06

    R&D partnership

    Building with institutions

    At the same table as TÜBİTAK, technoparks, and universities. We welcome institutional partnerships that turn research into products and feed them with field data.

    Talk about this discipline
AI & Research

From perception to decision.

AI isn't a garnish on our products — it's how they work. This is the path a raw signal travels before it becomes a product decision.

  1. 01 · Input

    Perception

    Camera frames, sensor output, text, and user interaction. Signal is captured where it is produced.

    • Vision
    • Sensors
    • Text
    • Interaction
  2. 02 · Data

    Data layer

    Captured signal is validated, normalised, and shaped into something a model can learn from.

    • Validation
    • Normalisation
    • Labelling
    • Storage
  3. 03 · Model

    Modelling

    Computer vision and natural language models. Anything that has to run close to the sensor is deployed as Edge AI.

    • Computer Vision
    • NLP
    • Edge AI
    • Evaluation
  4. 04 · Decision

    Decision support

    A model output is not an answer on its own. Thresholds, rules, and context turn it into something actionable.

    • Signal
    • Thresholds
    • Recommendation
    • Alert
  5. 05 · Product

    Product

    The decision surfaces on a screen someone already uses. AI is part of the flow, not a separate tab.

    • Interface
    • Notification
    • Report
    • Automation

Every stage is measurable. If we can't measure an output, it doesn't reach production.

Technology

One engineering stack, six products.

The products serve different industries; the layers underneath them are the same. It's the fastest way to carry what we learn in one product into the next.

Capabilities
  • Computer Vision
  • NLP
  • Edge AI
  • Cloud-Native
  • Type-Safe
  • CI/CD
  • Observability
  • Realtime
SezAI technology stack — layered architecture diagram
  • L5Product
    • iOS
    • Android
    • Web

    The layer people actually touch: mobile applications and web interfaces.

  • L4Application
    • TypeScript
    • React Native
    • Node.js

    End-to-end type safety. A client and server that share a language ship with fewer surprises.

  • L3AI
    • Python
    • Computer Vision
    • NLP
    • Edge AI

    Where models are trained and served. Workloads that need to run at the edge stay on the device.

  • L2Data
    • PostgreSQL
    • Redis
    • Firebase

    Relational persistence, caching, and realtime synchronisation side by side.

  • L1Infrastructure
    • Google Cloud
    • Docker
    • Vercel

    Containerised services, managed cloud, and an automated deployment pipeline.

Stack
  • Google Cloud
  • TypeScript
  • React Native
  • Node.js
  • Python
  • Firebase
  • PostgreSQL
  • Redis
  • Docker
  • Vercel
Infrastructure

Ready for the next user.

Scale is an architectural decision, not a marketing line. We build so that growth doesn't require a rewrite.

  • Cloud-native core

    Managed services and containerised workloads, so capacity is a setting rather than a migration.

  • Realtime flow

    Orders, attendance, reservations: when state changes, no screen should have to wait for it.

  • Caching layer

    Frequently read data never reaches the database. The cheapest latency you'll ever remove.

  • Relational persistence

    Schema-backed, verifiable storage for the data that demands consistency — finance and membership.

  • Observability

    Logs, metrics, and traces. Seeing a problem before your users do is half of fixing it.

  • CI/CD

    Every change takes the same route: automated checks, predictable deploys, fast rollback.

  • Containerisation

    Development, staging, and production run the same image, so “it worked locally” isn't an excuse.

  • Security and compliance

    Authorisation, data separation, and compliant storage are designed in, not bolted on.

Partners

At the table with institutions.

We work closely with Türkiye's research institutions, technology valleys, and universities. These partnerships feed our products with real-world signal.

Get in touch about a partnership
Why SezAI

Four decisions, six products.

Four principles that haven't changed since day one. They drive our product calls and our engineering calls alike.

  1. 01Product-led

    Product-led

    We own, use, and improve our own products. Whether a feature is right gets settled by usage, not by a brief.

    • Our own roadmap
    • Code with a long life
    • Direct user contact
  2. 02AI-native

    AI-native

    AI is the foundation of our products, not the decoration. We deploy computer vision, NLP, and decision-support models in real scenarios.

    • Computer Vision
    • NLP
    • Edge AI
  3. 03Cloud-native

    Cloud-native

    Cloud-native architecture, a type-safe codebase, and modern DevOps practice. Moving fast needs a foundation worth standing on.

    • Type safety
    • CI/CD
    • Observability
  4. 04Long-term

    Long-term

    We optimise for compounding value over short-term speed. Every product is designed as a seed for its own ecosystem, and the revenue model is built with the same discipline.

    • Subscription and usage
    • Ecosystem participation
    • New verticals
FAQ

Questions we get asked.

The ones that come up most from investors, institutions, and engineers.

  • SezAI is a technology studio building scalable, AI-driven digital products. Instead of running client projects as an agency, we own, build, and operate our own products — TeknoNext, KozmosDB, Erezervem, Helmet AI, CepteKampüs, and Piyyuu.

  • Computer vision, natural language processing, and models that run at the edge are our core areas. We pair them with embedded systems and place the output inside products as a decision-support layer. In KozmosDB, for example, NLP drives query generation; in CepteKampüs it powers exam and topic analysis.

  • Education (CepteKampüs, Erezervem), restaurant and retail operations (Piyyuu), developer tooling and data (KozmosDB), the technology community (TeknoNext), and R&D in computer vision and embedded systems (Helmet AI). What they share isn't a sector — it's the engineering stack underneath.

  • A cloud-native foundation on Google Cloud: TypeScript for end-to-end type safety, React Native on mobile, Node.js for services, and Python on the model side. PostgreSQL, Redis, and Firebase in the data layer, with Docker, Vercel, and an automated CI/CD pipeline for delivery.

  • Yes. We already work closely with TÜBİTAK, İTÜ, Bilişim Vadisi, Düzce Teknopark, Gaziantep Teknopark, and TİM. For deploying one of our products at your institution, joint R&D, or a pilot, choose “Corporate partnership” as the subject in the form below.

  • We do review investment, partnership, and collaboration enquiries. Reach us through the form or by email directly — we reply within one business day.

  • The form below is enough. If you describe which problem the idea solves and how it gets solved today, we'll come to the first conversation far better prepared.

Contact

Let's talk aboutthe next product.

We're here for investment, corporate partnerships, and product ideas. We reply within one business day.

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