Secure AI Hub
A governed gateway for approved commercial and open models, with access controls, routing policies, usage management and deployment flexibility.
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AI SaaS, secure model access, enterprise knowledge (RAG), voice and workflow agents, document intelligence and custom AI systems, deployed as managed SaaS, private cloud or self-hosted open-LLM hubs, and supported by Ledger Bytes engineering.
Durable enterprise capabilities rather than a list of model names.
A governed gateway for approved commercial and open models, with access controls, routing policies, usage management and deployment flexibility.
Permission-aware retrieval across documents and systems, with citations and controlled response generation.
Task-specific agents using approved tools, business rules, human approvals and auditable workflow state.
Inbound and outbound voice agents, chat assistants, scheduling, CRM integration and supervised escalation.
Classification, extraction, review support and structured workflow automation for operational documents.
Model and prompt evaluation, policy testing, red-team scenarios, monitoring and release gates.
Straightforward answers to common questions.
It builds private, model-neutral enterprise AI: a Secure AI Hub model gateway, enterprise RAG and knowledge assistants, AI agents and workflow orchestration, voice and customer-operations AI, document intelligence and AI governance, plus AI consulting and custom AI development, deployable as managed SaaS, private cloud or self-hosted open-LLM hubs.
Yes. The architecture is model-neutral and supports self-hosted and on-premises deployment of selected open-source LLMs and orchestration components inside client-controlled infrastructure.
Retrieval-augmented generation grounds AI responses in your own documents and systems. Ledger Bytes implements permission-aware retrieval with citations and controlled generation so answers stay accurate, attributable and within access boundaries.
No. Selection is based on data handling, quality, latency, cost, licence and governance. We use commercial, open or specialist models as appropriate.
Describe the workflow, users, data sources, intended actions and deployment boundary. The group team will coordinate AI, integration, software and regional requirements.