Services

Custom AI Development

Bespoke AI solutions built for your unique needs. From concept to production, we build systems that integrate seamlessly with your existing infrastructure.

See project types

When to build custom

Off-the-shelf AI solutions work for common use cases. But when your competitive advantage depends on AI that truly understands your domain, custom development delivers differentiated results.

85%
of enterprise AI requires customization
3-12mo
typical project timeline
10x
ROI on successful deployments
24/7
production support available
Project Complexity

Solutions for every scale

From focused pilots to enterprise-wide platforms, we scope projects appropriately.

Standard

Single use case with standard integrations

Document classification, sentiment analysis, basic chatbots

Timeline 3-4 months
Investment €50K - €150K
Complex

Multiple use cases or advanced requirements

Multi-modal systems, complex workflows, custom models

Timeline 4-8 months
Investment €150K - €400K
Enterprise

Mission-critical systems with extensive integrations

Platform-scale AI, real-time systems, regulated industries

Timeline 6-12+ months
Investment €400K+
Engagement Timeline

From concept to production

1

Discovery

2-4 weeks

Requirements, data assessment, architecture design

2

Prototype

4-6 weeks

Working proof-of-concept with your data

3

Development

8-16 weeks

Production-ready implementation with testing

4

Deployment

2-4 weeks

Go-live, monitoring setup, knowledge transfer

Who This Is For

Built for teams with vision

We partner with organizations ready to invest in AI that differentiates their business.

Product Leaders

Building AI-powered features that differentiate your product

Engineering Teams

Needing specialized AI expertise to augment your capabilities

Operations Leaders

Automating complex workflows with intelligent systems

Data Teams

Turning data assets into production AI applications

Solutions

What we build

From intelligent automation to complex reasoning systems, we build AI that solves real problems.

Conversational AI

Chatbots, virtual assistants, and customer service automation.

Document Intelligence

Extract, classify, and understand information from documents.

Recommendation Systems

Personalized recommendations for products, content, and more.

Computer Vision

Image classification, object detection, and visual inspection.

Predictive Analytics

Forecast demand, churn, and business outcomes.

Process Automation

Automate repetitive tasks with intelligent workflows.

What We Deliver

Production-ready deliverables

Production AI System

Fully deployed, tested, and monitored AI solution in your environment.

API & Integration Layer

Clean APIs for integration with your existing systems and workflows.

Documentation

Technical docs, runbooks, and architecture diagrams for your team.

Model Artifacts

Trained models, evaluation reports, and versioned checkpoints.

Monitoring Dashboard

Real-time visibility into model performance and system health.

Knowledge Transfer

Training sessions and handoff to enable your team to maintain the system.

Our Process

How we work

1

Discovery

Deep dive into requirements, data, and success criteria with your team.

2

Design

Architecture, model selection, and integration planning.

3

Build

Iterative development with regular demos and feedback cycles.

4

Deploy

Production rollout with monitoring, testing, and support.

Technology

Built with modern tools

We use industry-leading frameworks and infrastructure to build reliable, scalable systems.

PyTorch
TensorFlow
Hugging Face
OpenAI
AWS/GCP
Kubernetes
FastAPI
PostgreSQL
Prerequisites

What you'll need

Successful AI projects start with the right foundations.

Data Availability

Access to relevant training data or a plan to acquire it.

Clear Use Case

Well-defined problem with measurable success criteria.

Stakeholder Alignment

Executive sponsorship and cross-functional buy-in.

Build vs Buy

Build vs Buy: the hidden costs of generic solutions

Off-the-shelf AI often falls short when your needs are unique.

  • Generic models trained on generic data — not your domain
  • Limited customization options constrain your differentiation
  • Vendor lock-in and unpredictable pricing at scale
  • Integration complexity with your existing systems
  • No competitive moat — your competitors use the same tools

Executive Takeaway

Custom AI development is an investment in competitive advantage. When done right, it creates defensible value that generic solutions cannot replicate.

1
Identify use cases where AI differentiation matters most
2
Assess your data readiness and availability
3
Build a business case with clear ROI metrics
4
Start with a focused pilot before scaling
Custom Development

Let's build something remarkable

Share your vision and we'll help you bring it to life.

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