Data and retrieval foundation
Connect documents, databases, events and APIs into a governed knowledge layer with permissions and citations.
AI platform development
Build a custom AI platform your company can actually run.
ROTZ.AI designs and builds production AI platforms with secure data foundations, LLM orchestration, dashboards, MLOps and governance.
Custom platforms · LLM apps · vector search · MLOps · governance
Built for production ownership
Model-agnostic architecture
Secure integrations with your existing systems
AI platform development
A platform is different from a demo
A serious AI platform connects models, data, permissions, workflows, user interfaces and monitoring into one operating system for intelligence. It needs to be reliable enough for teams to use every day.
ROTZ.AI builds custom AI platforms for companies that need domain-specific workflows, internal copilots, intelligence dashboards, retrieval systems, model evaluation and integration with existing tools.
We design for portability from the start: swappable models, observable pipelines, documented architecture, controlled cost and clear internal ownership.
AI platform capabilities
Model orchestration
Route tasks across LLMs, classical models, tools and human approval steps with evaluation and fallback paths.
User-facing product
Dashboards, copilots, admin surfaces and workflow interfaces designed for repeated operational use.
MLOps and observability
Deployment, logs, traces, prompt/version control, cost tracking, quality evaluation and incident response.
From architecture to launch
01
Define the platform boundary
We decide what the platform owns, what it integrates with and what success means.
02
Build the foundation
Data, identity, retrieval, model routing and infrastructure are created before feature scale-out.
03
Ship core workflows
We release the first high-value workflows with evaluation and operational controls.
04
Scale safely
We add teams, use cases and models without losing governance, performance or cost control.
Platform build questions
Should we buy or build an AI platform?
Buy when the workflow is generic. Build when your data, process, governance or differentiation is specific to your business.
Can the platform use multiple models?
Yes. We design model-agnostic routing so OpenAI, Anthropic, Google, open-source or on-prem models can be swapped by use case.
Can internal teams maintain it?
Yes. Documentation, observability and ownership transfer are part of the platform plan.