Internal AI Platform Development

We design and deploy artificial intelligence systems: from prototype to production-ready solutions. Our team combines expertise in machine learning, data engineering and MLOps to make AI work not in the lab, but in real business.
8+Years of work900+Completed projects100+In house employees19+Partners
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Internal AI Platform Development
Complex
from 2 weeks to 3 months
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AI Development Areas
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Internal AI Platform Development

Internal AI platform is centralized infrastructure giving all company teams access to AI tools through single interface. Alternative: each team uses ChatGPT in browser, data goes to OpenAI, cost uncontrollable, no compliance. We build corporate AI hub.

What's Included in Internal AI Platform

Model Gateway: Single endpoint for model access: GPT-4o, Claude, Llama 3 (self-hosted), Mistral. Rate limiting per department, cost allocation, audit log of all requests. SSO integration (SAML/OIDC).

Knowledge Base (RAG): Vector store of corporate documents: internal wiki, SOP, technical documents, legal documents. Access control — department A doesn't see department B documents. Automatic indexing from Confluence, SharePoint, Google Drive.

Team Tools:

  • Developers: code review, docstring generation, test generation
  • HR: resume screening, JD generation, onboarding assistant
  • Legal: contract review, summarization
  • Customer Support: answer generation from knowledge base
  • Analytics: natural language to SQL, report generation

Admin Panel: Rights management, quotas, usage monitoring by teams, cost breakdown, performance models (which teams use AI most effectively).

Architecture

On-premise / Private Cloud Deployment: All data stays in company infrastructure. Self-hosted LLM (Llama 3 70B, Mixtral 8x7B) via vLLM + Kubernetes. For tasks requiring GPT-4 level — Azure OpenAI with data privacy agreements.

Self-hosted Vector Store: Qdrant or Weaviate on own servers. No data in third-party cloud.

Pipeline for 12–16 Weeks

Weeks 1–4: Infrastructure setup. Model gateway. SSO. Basic chat interface.

Weeks 5–9: Knowledge base RAG. Document ingestion from corporate sources. Access control.

Weeks 10–13: Team-specific tools. Admin panel. Usage analytics.

Weeks 14–16: Security audit. Employee onboarding. Change management.

ROI of Corporate AI Platform

In our practice: 2–4 hours saving per week per employee. With 100-person team — 200–400 hours/week. Centralized cost control reduces AI spending 30–50% vs. chaotic individual subscriptions.