All-in-One Platform for Building
Most leaders know AI can help. Fewer know who should build it, keep it safe, and make sure it still works six months from now. That's our job. One team, one place, for every piece of AI your business runs on.
The kind of work we take on.
Most of what we build falls into four shapes. Each one started with a specific problem someone walked in with.
Conversational agents
Where most support and operations work happens.
Customers, vendors, suppliers, all asking the same questions. An agent can handle the repetition, act on what it hears, and hand back anything that needs a person.
- Multi-turn reasoning
- Tool use across your stack
- Human approval on sensitive replies
Analysis and reports
A junior analyst's work, without the ramp time.
Gathers from your systems and the web, writes up what it found, flags what matters. You review and act.
- Web and internal data
- Custom external integrations
- Structured, reviewable output
Internal knowledge copilot
Knowledge trapped in heads and folders.
An agent grounded in your documents answers the questions employees used to send to a colleague, and cites where the answer came from.
- Grounded in your docs
- Role-aware access
- Citations on every answer
And more
The shortlist is long.
Recovery, research, onboarding, compliance, operations. If it involves reasoning or a multi-step process, it's usually a fit. Tell us what's on your mind.
What teams usually notice.
A few things that show up consistently after the first few weeks.
Faster response times
Customers get answers in seconds instead of waiting in a queue. Agents reply the moment a request comes in.
Less work for support
Repetitive tickets get handled automatically. Your team focuses on the cases that actually need a human.
Real cost savings
You stop paying for work that can be automated. Most teams see the saving within the first few weeks.
Three building blocks. Everything else is combinations.
You don't need to understand how the platform works. But if you're curious, these are the three pieces we use to build everything.
Workflows
The predictable parts.
Flows that run the same way every time. Ticket triage, invoice routing, onboarding. When the steps are known, we set them in stone.
- Fixed sequence of steps
- Triggers from Gmail, Stripe, APIs
- Full audit log on every run
AI Agents
The parts that need judgment.
Give an agent a goal and the tools. It works out the steps, takes the safe ones, and escalates anything that needs a person.
- Reasons through goals
- Uses tools and integrations
- Human approval on sensitive actions
Data Stores
Your company's memory.
Your documents, policies, and history. Agents search and cite them, so answers come from your truth rather than the internet's.
- Semantic search over your data
- Auto-sync from your tools
- EU-hosted, never used for training
How engagements usually go.
Most of them look roughly like this.
A short conversation
We understand what's in your head, point at the first thing worth automating, and agree on what a good outcome looks like.
We build it
Our team builds the agent or workflow on our platform, integrated with your tools. You don't manage it.
You review
We show you runs on your real data. You tweak, sign off, or tell us it's not ready yet.
It goes live
We roll it out, watch every run, and iterate weekly. You see everything from day one.
Then we stay. Whenever AI is the right tool for something else, you know who to call.
Most AI projects we see get stuck somewhere between the idea and production. Either the team knows the platform but not the business, or the other way around.
We built Workerflow to close that gap. We still run every engagement personally. If you're thinking about AI for your company and you're not sure where to start, write to us. The conversation is free, and useful even if you end up doing nothing.
Ivaylo, founder
A conversation, not a pitch
We work with a small number of companies at a time. Tell us what's on your mind, however rough. We'll reply with a thought, a question, or a proposal, whichever feels right.