AI INTEGRATION
Most mid-market businesses know they need AI. Few know where it actually makes a difference. We identify exactly where it creates value in your operations, then build it.
This service is for companies that…
- Feel the AI pressure
- Understand they could improve their processes with AI
- Lack the necessary technical skill to implement AI into their business
Departments we can transform with AI
Sales and Marketing
Your teams spend more time on research, data entry, and reporting than on the work that actually moves revenue. We build agents that handle the mechanical layer: enriching contact and company data, tracking signals across channels, and keeping reporting current. Your team focuses on strategy, relationships, and closing.
Operations
Orders, requests, and data arrive in different formats from different channels, and someone has to read them, interpret them, and enter them somewhere. We map where those manual steps are and replace them with agents that read inputs regardless of format, extract what’s relevant, and route it automatically. The work stops depending on a specific person being available.
Finance and Accounting
Finance teams process documents that arrive in inconsistent formats and require significant manual handling. We build agents that read invoices, receipts, and contracts, extract the relevant fields, match against existing records, and flag anything that needs a decision. Processing time drops sharply, and nothing falls through because someone was busy.
Customer support
Support teams face a volume problem: demand grows, headcount doesn’t, and response quality varies by day and person. We build agents that draft ticket responses from your knowledge base and customer success systems that flag at-risk accounts before the renewal conversation gets difficult. Your team spends its time on the work that actually needs a person.
Human resources
HR teams field the same questions repeatedly, spend hours screening CVs, and watch new hires struggle to find answers in their first weeks. We build systems that handle all three: policy questions answered from your actual documentation, CVs screened against real job requirements, and onboarding support that gives new hires answers instantly.
The Process — How we help you integrate AI
01
PROCESS MAPPING
We spend time with your team learning how they work: where decisions get made, where data comes from, and where people are doing things manually that shouldn’t require a person. This phase isn’t about technology yet. It’s about understanding the problem well enough to solve it properly.
Key activities:
- A staged rollout to a defined user group
- Usage monitoring and pattern analysis
- Agent iteration based on feedback
02
DATA ANALYSIS
Every AI solution we build reasons from data. If that data is incomplete, inconsistent, or structured the wrong way, it will fail regardless of how well it’s built.
We audit what you have, identify what needs cleaning or restructuring, and build the foundation before we build anything else. This is the step most implementations skip, and the reason most of them disappoint.
Key activities:
- Data source audit across your systems
- Quality assessment and gap analysis
- Data preparation and structuring
03
Solution development
We design and build the solution: the agents, the data connections, and the logic that handles your specific process. We keep the initial scope tight so you see something working quickly and have something real to react to before we go further.
Key activities:
- Agent design and development
- System and data integrations
- Testing against your real processes
04
Deployment and improvement
We release it to a small group first and watch how they use it. Real usage reveals things a spec never does: people find unexpected paths, and edge cases appear. We feed that back, update the system, and run the loop again until it can handle what it was built for reliably and efficiently.
Key activities:
- A staged rollout to a defined user group
- Usage monitoring and pattern analysis
- Agent iteration based on feedback
We did it for ourselves first…
We’ve tackled AI from top to bottom. It all started with our founder, Marko Strizic, who spent five months immersed in it before we offered this as a service, building and testing it against real problems in our own business.
This transformed key departments across the company: sales, marketing, and engineering. Our development teams have adopted agentic development processes, and we’ve saved hundreds of hours of manual work across non-technical functions.
What started as a founder’s hands-on drive to understand new technology has become a company-wide transformation. And we can do the same for you.
…Then for our clients
Built an all-in-one business platform for a $50M-funded AI startup →
We partnered with an Australian AI startup to build a unified business platform, where we expanded their engineering capacity and delivered key AI features using Ruby on Rails, React, and major AI integrations.
Industry
AI Software
Location
Australia
Co. type
Post-IPO
Designed and built a scalable AI health platform →
We built a platform that helps health professionals assess clients through structured questionnaires, review results, and create personalized supplement plans. It connects to the client’s product catalog, supports ordering, and includes tools like scheduling, client dossiers, and AI-assisted notes.
Industry
HealthTech
Location
Netherlands
Co. type
SME
Great, but why DECODE?
Here’s why you should hire us for your AI software development needs:
Senior engineers, not AI consultants
We’ve been building software for 14 years, long before AI came into the picture. That means we’re not asking AI how to build great software; we’re instructing it how to do it.
We pull the reins on AI
Powerful tools can tempt you to automate everything at once. But the right approach is narrower and more deliberate. We’ll tell you when something isn’t worth building.
Delivered for the best
We’ve developed software for Microsoft, Royal Caribbean, and AT&T. We’ll apply the same engineering rigor to your software solution.
OUR AI TECH STACK
Platforms
OpenAI
Anthropic (Claude)
Gemini
Hugging Face
Llama
Frameworks
PyTorch
TensorFlow
LangChain
Streamlit
Databases
PostgreSQL
MySQL
Cassandra
Redshift
Vector databases
Pinecone
Qdrant
Chroma
How we use AI across the software development lifecycle
We use AI throughout the software lifecycle to reduce repetitive work and put more time into quality, product thinking, and better decisions.
In this article, we break down how that works across planning, design, development, testing, and post-launch support, and where agentic development fits into the way we build.
This could be the start of a great partnership
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Arrange a chat with Ivor, our client strategy specialist.