wildstyle network
    AI Technology
    Artificial Intelligence

    TECHNOLOGY

    We build AI systems that work inside your infrastructure. Agents, custom models, RAG pipelines and internal platforms. Designed for your data, your workflows and your security requirements.

    Discuss your use case
    Why custom AI

    Off-the-shelf AI tools work for experimentation. Operational systems require more.

    When AI needs to access internal data, follow compliance rules, integrate with existing systems and run reliably at scale, generic tools reach their limits. Custom AI systems are built for your specific context.

    Every system we build starts with your data, your workflows and your infrastructure. The architecture depends on the problem, not on what is trending.

    Internal data integration
    Security and compliance
    Workflow automation
    Model control
    Capabilities

    What we build

    AI Agents

    Autonomous systems that execute multi-step tasks across tools and data sources. Built on LangGraph and custom orchestration frameworks

    Custom Models

    Fine-tuned LLMs trained on your domain data. Higher precision, lower latency and full control over outputs and model behavior

    RAG Systems

    Retrieval-augmented generation pipelines connected to internal knowledge. Hybrid search, reranking and citation tracking built in

    AI Platforms

    Internal tools for managing prompts, workflows and model access across teams. Version control, monitoring and usage analytics included

    AI architecture
    Architecture

    Selected by requirements, not by trends

    Every goal and system combines different components. LLMs, vector databases, RAG pipelines and agent frameworks are selected based on user journey, working process, data structure, latency requirements and compliance constraints.

    Integration

    AI connects to what already works

    We build systems that plug into your existing tools. CRM, CMS, knowledge bases and data warehouses become data sources for intelligent automation. Nothing gets replaced. AI leverages what is already there.

    AI integration
    Technology

    Our engineering stack

    Model Families

    GPT, Claude, Gemini
    Mistral, Llama, Qwen
    Custom fine-tuned models
    Multi-model and -tool orchestration

    Infrastructure

    Azure, IONOS, Google
    LangChain/Graph, MCP, N8N
    REST, GraphQL, webhooks
    Docker, Kubernetes

    Capabilities

    Agentic workflows
    Automation
    Model training
    Working Dashboards

    Integration

    CRM and CMS platforms
    Internal knowledge bases
    Sales tools
    Communication tools
    Track Record

    Production-grade AI engineering

    3 weeks

    average time from kickoff to working prototype

    99.5%

    uptime across production AI deployments

    Use Cases

    What teams build with us

    Branded Knowledge Assistants

    AI assistants that answer employee questions based on company documentation, policies, and internal knowledge

    Sales RFP Intake Workflow

    An AI-supported sales workflow that reviews RFP documents, identifies relevant solution components, and helps structure tailored offers

    Energy Product Sizing Configurator

    A configuration tool that gathers product and project data from multiple sources, structures it, and supports sizing and comparison

    Multi-Model Council Chat

    A collaborative chat environment where multiple language models respond to the same prompt for comparison and decision support

    AI Media Creation Pipelines

    Automated content pipelines for video production, where teams define story, style, and setting while AI generates supporting media assets

    Brand Voice Translator

    A language model tuned to translate from English into multiple languages while preserving brand voice, terminology, and style

    Build AI systems
    that work

    Tell us about your use case. We evaluate feasibility and build a working quick-start prototype.

    Get in touch