The Platform
The trust infrastructure for enterprise AI.
Eight capabilities. One tenant-isolated data plane. Engineered so every answer, document, workflow, and decision can be verified, governed, and trusted.
Agentic AI
Autonomous agents that plan, verify, cite, and act. Every action is explainable, auditable, and reversible — with human review built in.
Multi-LLM Architecture
Route across GPT, Claude, Gemini, Grok, Llama, Mistral, DeepSeek, Command, Qwen, Phi. Compare accuracy, cost, latency, and hallucination in real time.
RAG
Retrieval-augmented generation across every enterprise source. Chunk, embed, index, dedupe — with provenance carried through every answer.
Knowledge Graph
Entities, relationships, and lineage over your documents, wikis, and sites. Traverse from any answer back to every source that shaped it.
Semantic Search
Dense + sparse + graph retrieval. Understand intent, not just keywords — across every document, tenant, and language.
Trust Score
A composite indicator across originality, integrity, readability, compliance, quality, and verification signals — decision-support at a glance.
Governance
Policy, cost, prompt, model, and data governance — enforced organization-wide with immutable audit and RBAC.
Security
Row-level security, AES-256 encryption, SSO/SCIM, secrets vault, and deployment options from shared SaaS to on-premise.
Responsible AI
Four principles. Enforced by architecture.
Humans Remain Responsible
AI should assist human judgment, not replace it. Every high-impact decision keeps a human in the loop.
Explainability
Users should understand how results were generated — with citations, sources, and confidence surfaced everywhere possible.
Transparency
Evidence, sources, citations, and confidence scores are visible by default — never hidden behind a black box.
Verification
AI outputs should be verified before action is taken. The platform is engineered to enable — and often require — human review.