The architecture behind
specialized intelligence.
Explore every layer of the Arivonix platform — the institutional knowledge and models that flow in, the specialization engine at its core, the agent runtime, and the channels that embed intelligence directly in your workflows.
Building this from scratch typically costs $1M+ in engineering and 12 to 18 months to production. Arivonix has built it, so your team starts at the specialization step, not the infrastructure one.
What flows in
Your data, any model, and your existing systems — with zero data movement, inside your environment.
Institutional knowledge
- Knowledge graph, ontologies & taxonomies
- Documents, policies & runbooks
- Catalog, lineage & vector indices
Models
- LLMs & SLMs — frontier, open-source, hosted
- Embedding, vision & multimodal
- Model registry, versioning & serving
Integrations
- 250+ connectors, multi-cloud
- CRM, ERP, databases, SaaS, collaboration
- Real-time + batch, streams & events
Where models meet your knowledge
The specialization engine turns general-purpose models into ones that reason in your domain.
Language Model Designer
- Fine-tune LLMs & SLMs on your knowledge
- Train, adapt, align, evaluate
RAG & embeddings
- Hybrid retrieval with citations
Prompts & tools designer
- Skills, templates, MCP
Knowledge graph builder
- Semantic reasoning over your data
Guardrails
- Safety, PII, policy enforcement
Data pipeline designer
- 250+ transformations, synthetic data, feature prep
Evaluation harness
- Benchmarks, LLM judges, regression tests
Specialized agents at work
Agents plan, collaborate, and run your workflows — with humans in the loop where it matters.
Agent catalog
- 200+ system + custom domain agents
Orchestration & routing
- Plan, route, supervise, escalate
Multi-agent protocol
- A2A messaging, shared memory
Workflow + HITL gates
- Long-running, approvals, review, override
State & context
- Sessions, memory, long-term recall
Embedded in your workflows
Specialized intelligence reaches your people and systems — programmatic or conversational, all in your environment.
AI search & chatbot
- Conversational UX over your knowledge
GenAI analytics
- Natural-language queries on your data
Knowledge graph UI
- Semantic explorer
REST APIs & cleanroom
- Programmatic access + secure share
Self-service BI & notebooks
- Analyst workbench
Embedded & external
- SDK, webhooks
Observability & feedback
Every interaction is observed and scored, then fed back so your agents keep improving.
Agent traces & spans
- Tool calls, latency, tokens
User feedback
- Ratings, corrections, edits
Quality & eval scores
- LLM judges, human raters
Drift & anomaly detection
- Behavior shifts, regressions
Reinforcement signals
- Preference data → DPO / RLAIF
↑ Feeds back into the Specialization core to retrain and realign your models.