We’re building the
operating layer for AI agents
Korelos AI Studio was born from a simple frustration: deploying useful AI should be as easy as calling an API. We’re on a mission to make autonomous AI agents accessible to every developer and business in the world.
How it started
The idea for Korelos came from watching brilliant teams waste months reinventing the same infrastructure before they could ship a single useful AI feature.
In 2025, our founders were working with a series of startups trying to integrate AI agents into their products. Each team faced the same challenges: they had to build their own orchestration layer, manage memory across conversations, wire up tool integrations, handle retries, and set up observability — before they could even test whether their agent idea actually worked.
What should have been a two-day experiment turned into a two-month engineering project. Every. Single. Time.
We asked: what if all of that was just an API call? What if you could define an agent, give it tools, and have it live in production within minutes — not months?
That question became Korelos AI Studio. A platform where the hard parts — infrastructure, scaling, memory management, observability, tool execution — are handled for you. So you can focus entirely on what your agent does, not on how to keep it running.
Korelos AI Studio
Launching Mid 2027
The problem identified
Founders observe the same AI infrastructure problem across dozens of teams.
First prototype built
Internal version created and tested with three pilot companies. Reduced deployment time from 8 weeks to 2 days.
Platform development
Full platform built — REST API, Studio portal, multi-model support, persistent memory, and observability.
MVP under construction
Pre-launch development continues. The waitlist is open and the team is shipping toward a developer beta.
Developer beta
Opening access to waitlist members ready to build the next generation of AI-powered workflows.
Built by builders, for builders
Korelos is built by a small founding team that pairs hands-on customer experience with deep production engineering — the same combination most AI tools are missing.
Waleed Ghaffar
Waleed spent the early part of his career in SEO, doing technical work for clients ranging from small e-commerce shops to growth-stage SaaS companies. Most of the job, he found, was writing small scripts and automation glue to handle work that should have been a single click or a single API call. The same pattern showed up later when he started experimenting with AI agents. The underlying models were getting better fast, but the tooling around them was still a tangle of orchestration code, custom retry logic, and brittle integrations.
He started Korelos to skip past that part of the work. The bet is simple: most teams don’t actually want to build agent infrastructure, they want to build agents. He spends most of his time talking to early customers, writing docs, and pushing the product in a direction that solves real problems instead of chasing trends.
Hussein Aalee
Hussein is a software engineer who has spent the last several years building backend systems and, more recently, production AI agents. Before Korelos he worked across a mix of startups, mostly on the parts of an application nobody talks about until they break: queues, schedulers, data pipelines, and the integration layers between them.
He came to AI agents the same way most engineers do, by being asked to ship one quickly and discovering that the existing tooling was nowhere near production-ready. At Korelos he owns the technical roadmap, the agent runtime, the API, and the infrastructure that keeps everything running. He cares about reliability more than novelty. If it can’t be debugged and recovered at 3am, it doesn’t ship.
Follow us on LinkedIn · We’re hiring — support@korelos.com
AI is powerful. Deploying it is painful.
Today, turning an AI idea into a production-ready agent requires significant engineering investment. Most teams are rebuilding the same foundational components from scratch — over and over.
- Weeks building custom orchestration layers
- Complex memory management across sessions
- Building and maintaining tool integration wrappers
- Zero observability into what agents actually do
- Scaling infrastructure for every new agent
- Rebuilding auth, retries, and error handling
- Different code for every AI model provider
- Agent live in minutes with a single API call
- Persistent, scoped memory built in by default
- Register any tool once — agents call it automatically
- Full execution traces and analytics out of the box
- Auto-scaling infrastructure, no ops required
- Resilient execution with retries handled for you
- Swap models per-agent without changing your code
What we stand for
We believe AI agents should be as easy to deploy as a web service. Our values guide every decision we make — from product design to how we treat customers.
Simplicity over cleverness
The best infrastructure is invisible. We obsess over reducing complexity so developers can focus on building, not debugging abstractions.
Reliability is non-negotiable
Production AI systems need to work every time. We build for 99% uptime and treat every failure as a personal failing.
Democratize AI operations
Enterprise-grade AI infrastructure shouldn’t require an enterprise budget. We build for the solo developer and Fortune 500 alike.
Full transparency
You should always know what your agents are doing and why. Every decision, tool call, and output is traceable and auditable.
Developer-first
We make decisions by talking to developers. Our API design, documentation, and support all start with what makes your life easier.
Ship fast, iterate faster
The AI landscape evolves weekly. We commit to shipping improvements fast and keeping pace so you always have access to the best models and tools.
Where we’re going
Korelos AI Studio is just the beginning. Here’s what we’re building toward — in the short, medium, and long term.
Launch the world’s simplest agent API
Make deploying an AI agent take 5 minutes and 5 lines of code. Set the industry standard for what agent-as-a-service means — clean, predictable, and production-ready from day one.
Build the richest tool integration ecosystem
Create a marketplace of pre-built tool integrations — from databases to SaaS apps to internal APIs — so developers can connect anything in minutes, not days.
Enable multi-agent orchestration
Allow agents to spawn, call, and coordinate with other agents. Build complex workflows where specialized agents collaborate.
Power 100,000 production agents
Become the infrastructure layer running agents for startups, enterprises, and everything in between. Prove that reliable, scalable AI operations are within reach for every team.
Make agents self-improving
Build feedback loops that let agents learn from their runs, improve their tool usage, and surface optimization suggestions — so your agents get better over time automatically.
Ready to build with us?
Join the waitlist and be part of the first wave of developers shaping the future of AI agents.