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Appumia
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Generative AI for organizations

Put AI to workwithout your data leaving home.

From local LLMs running on your own servers to cloud models, from customer-facing chatbots to end-to-end enterprise software — we design, deploy and operate the AI solution that fits your needs.

Free intro callExplore services
  • On-prem / hybrid deployment
  • Privacy-first architecture
  • Open-source & commercial models

Services

From idea to production, one team.

Model selection, infrastructure, integration and interface — we handle it all together.

  • Local LLM Solutions

    We deploy open-source models on your own servers or private cloud. Your data never leaves the organization.

    • GPU / hardware sizing
    • Model selection and fine-tuning
    • RAG over internal knowledge

  • Cloud LLM Integrations

    We connect leading cloud LLM providers to your systems — secure, scalable and cost-controlled.

    • API integration and orchestration
    • Data masking and access control
    • Usage and cost monitoring

  • Chatbots & Assistants

    Smart assistants that know your documents — on your website, WhatsApp or internal tools.

    • Multi-channel deployment
    • Knowledge base integration
    • Hand-off to human agents

  • Enterprise Software

    Custom web apps, dashboards and integrations built around your processes — AI or not.

    • Custom web & dashboard apps
    • ERP / CRM integrations
    • Process automation

Why Local LLM

Keep control of your data.

For organizations working with sensitive data, bringing the model to the data is often a better choice than sending the data to the model.

Not every scenario needs local. We decide on local, cloud or hybrid architecture together, based on your needs.

  • Privacy & data sovereignty

    Personal and business data is processed on your infrastructure, minimizing cross-border transfer and third-party risk.

  • Predictable cost

    Fixed infrastructure cost instead of pay-per-token. At high volumes, total cost can drop significantly.

  • Full customization

    Fine-tune the model to your terminology and workflows; versions and behavior stay fully under your control.

  • Air-gapped operation

    Deployments that run even in isolated environments with no internet connection.

Use cases

AI that works today.

We focus on applications that deliver measurable business results, not flashy demos.

  • Customer service

    24/7 support assistant

    A chatbot that answers common questions instantly and hands off to an agent when needed.

  • Knowledge management

    Internal document assistant

    A RAG-based assistant that answers from your policies, contracts and procedures — with sources.

  • Operations

    Process automation

    Workflows that classify, summarize and route emails, forms and documents into the right system.

  • Data & reporting

    Natural-language data queries

    An analytics assistant that lets managers query databases and reports in plain language.

Process

Start small, prove it, scale.

Every project starts with a short proof of concept (PoC) so risks surface early.

  1. 01Week 1

    Discovery

    We clarify needs, data sources and success criteria together.

  2. 02Weeks 2–4

    PoC

    We build a prototype on your real data and measure the results.

  3. 03Per project

    Integration

    We connect the solution to your existing systems and go live.

  4. 04Ongoing

    Support

    Monitoring, model updates and continuous improvement.

FAQ

Frequently asked questions

What hardware do we need for a local LLM?

It depends on user count, model size and expected response speed. During discovery we measure your needs and decide together whether your existing servers suffice or a new GPU investment makes sense.

Are local models as good as cloud models?

Current open-source models perform very well on many enterprise tasks, especially when grounded in your internal documents (RAG). For very broad, complex tasks cloud models may lead — which is why we also recommend hybrid architectures.

Will our data be used to train models?

With local deployments your data stays solely on your infrastructure. For cloud integrations we choose enterprise API options that do not retain or train on data, and we mask sensitive fields.

How long does a project take?

A PoC typically takes 2–4 weeks. Time to production depends on integration scope; we share a clear timeline after the discovery call.

Can it integrate with our existing software?

Yes. We integrate with ERP, CRM, document management systems, databases and messaging channels via APIs or custom connectors.

Contact

Let’s talk about your project.

Briefly describe what you need; we’ll get back to you within one business day.