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INTEGRATIONS · AI readiness
AI tools are available to everyone – your data gives you the edge.
Most companies fall short, and not because of AI’s limitations, but because
their systems were never designed to share data with it.
DOES THIS SOUND LIKE YOU?
Every major AI provider sells a model trained on the same public data anyone can license. Buying the tool puts you exactly where your competitors are. The only way to actually pull ahead is to run that tool on data nobody else has. Your clients. Your operations. Your history.
That’s the part most companies never reach. Not for lack of ambition, every board meeting has an AI agenda item by now, but because the systems holding that data were built for a different era, long before anyone imagined they’d need to talk to an AI model. You can license the most advanced model on the market. It still has to go through a system that was never designed for this, and without the right bridge between them, neither understands the other.
SOUND FAMILIAR?
“We already have the AI tools. We just don’t have our own data in them.”
“The IT department keeps telling me our system isn’t built for AI.”
“We tried an AI tool. Decent results, but someone still has to feed it the data by hand.”
“Every competitor is already trying AI. Is our IT landscape even ready for this?”
THE AI READINESS CURVE
Level 0 or 1 is where most mid-market companies actually sit. That’s usually why they start looking for outside help.
Silos. Manual data handling, nothing exposed. The only way to use AI with your own data is copying and pasting it in by hand.
Scripted Connections. Rigid, custom-coded links between a few tools. AI can use pieces of your data for isolated tasks, but one broken link breaks the whole chain.
Connected Infrastructure. Your systems are able to expose and accept data reliably, with no gaps. AI can get a full, trustworthy view of your data, but someone still has to ask for it.
Workflow Automation. Systems trigger each other and act automatically, no manual step in between. AI can act on its own, using your own data, safely and in real time.
How we build your foundation for AI.
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1
Check where your systems stand with AI | 2-3 weeks
We look at what your core systems can actually expose and accept, not just what’s on paper. Our team maps what your systems can actually connect to, where your data lives, and where the biggest gaps are between what AI needs and what you can currently deliver. This works best with direct access to the people who run these systems day-to-day; documentation alone rarely tells the full story. You get a clear picture of what’s realistic to fix first.
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2
Build the connections AI actually needs | months 1–4
We start with whatever we agreed was realistic to fix first, connecting your core systems using modern workflow automation and replacing brittle manual bridges with reliable, secure data flows. Your systems learn to expose what they know and accept instructions back, without a rewrite of what already works.
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3
Let AI use what only you have | months 4-6
With your systems connected and the manual bridges gone, your proprietary data becomes something AI can securely access, exactly when it’s needed. You’re no longer running the same public tool as everyone else, you’re running it on the one thing your competitors don’t have.
Ready to talk through it?
You already know AI is coming, one way or another. What you might not know is whether your systems can actually support it once it’s here. Walk us through what you’re trying to build with AI, and we’ll tell you exactly what your infrastructure is missing.
WHO WE ARE
We are an AI-accelerated nearshoring partner, headquartered in Berlin, with 100+ engineers and 15+ years of experience. Our engineers continuously train on new AI tools and stay close to where the field is heading, backed by 5+ years of hands-on experience connecting enterprise systems. Our engineering teams operate across Serbia and Bosnia & Herzegovina. We know exactly where integrations tend to fail and what it takes to keep them running. We offer both dedicated integration engineering teams and managed integration projects, depending on what works best for your organization.
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