Mission
Build AI that works inside real operations. Not lab experiments, not pilots that impress in a meeting — production tools that show up in daily work and stay useful as your business changes.
About Madency
An AI integrator built on 11 years of software discipline.
We build AI agents that work inside your operations — answering questions, taking actions, integrating with your tools, and proving themselves through daily use. Not demos, not pilots, production systems that earn their place.
Our story
Madency was founded in 2015 in Kyiv, Ukraine, as a custom software company. Over 11 years we've shipped more than a hundred projects across industries — e-commerce platforms, marketplaces, mobile apps, media products, smart vending systems, internal business tools. Different problems, different stacks, one underlying skill: taking complex operational reality and turning it into software that actually works.
In the past two years, the technology we work with has shifted. AI agents, vector databases, LLM orchestration, retrieval pipelines, tool-calling architectures — the toolkit looks nothing like what we built a decade ago. The discipline behind it hasn't changed.
Today our production work is AI agents that live inside business operations. Some answer questions — pulling information from CRMs, databases, documents, and chat tools to give your team clear answers in plain language. Others take action — updating records, sending follow-up emails, calling external APIs to generate quotes or scores, triggering downstream workflows. Most do both. The pattern is consistent: agents that close the loop between scattered information and the work that needs to happen.
Principles
What we stand for
We finish what we start.
In 11 years, we've never abandoned a project mid-flight. When something goes harder than expected — and it does — we absorb the cost rather than push it onto the client. It's not always profitable. It's the only way we know to build a track record that means something.
We go deep into your business.
We research your industry, study your competitors, ask questions until we understand how your team actually works — not how an org chart says they do. AI agents fail when they're built on the org chart. They work when they're built on the actual workflow.
We embed inside your operations.
Most clients know AI matters, but not what to build first. We embed alongside your team, watch how work actually happens, and identify where agents can create real value. By the time we ship, we understand the business well enough to keep improving the system beyond the original scope.
We think in years, not sprints.
Our longest client relationships are over 10 years old. That kind of continuity only happens if you stay useful long after the original project ships — which means caring about your business in five years, not just the demo next week.
Trusted by founders and operators across the US, UK, EU, and Ukraine
The team
A group of senior practitioners working in close collaboration. The core team that scopes your project stays involved in building it. If specialists are engaged, they work under the same confidentiality and IP obligations, with Madency responsible for their work.
AI Strategy & Audit
We map your operations, data sources, bottlenecks, and business goals to identify where AI agents can create measurable value. This is where vague AI ambition becomes a practical implementation path.
Agent Engineering
We design and build production AI agents that can retrieve information, reason over business context, call tools, update systems, and operate inside your existing workflows.
Product & UX
We turn complex AI capabilities into usable interfaces and interaction patterns your team can trust. The goal is not just powerful automation, but systems people actually adopt.
Infrastructure & Operations
We handle deployment, integrations, monitoring, access control, and reliability. AI systems need to keep working after launch, so production operations are part of the build from day one.
Security
How we handle your data
Your business data is sensitive. We treat it that way.
NDAs are standard from the first conversation. Production systems we build use encryption in transit and at rest, role-based access controls, and audit logging. We design every agent with data minimization in mind — it accesses what it needs to do its job, nothing more. We don't train models on your data.
If your industry has specific data handling requirements, raise them in Discovery. Most security questions have a clear answer. The ones that don't — we work through together before anything gets signed.
The track record
2015
Founded
100+
Projects shipped
10+ years
Longest single client engagement
Talk to us
If you have an operational problem that looks like an AI problem — or you just want to know whether AI can help your business right now — the fastest way to find out is a 30-minute conversation.
Discuss Your WorkflowDiscuss Your Workflow