A domain-specific model, fine-tuned on your data, encrypted inside your infrastructure. Nothing you know ends up inside someone else's model.
Brain
A small language model fine-tuned on your institution's data, terminology, and decision patterns. Not a general-purpose frontier model prompted into shape — a purpose-built model whose weights encode your domain knowledge directly. Operates efficiently on local hardware with drastically reduced hallucination rates.
Memory
A dual-layer memory system. The vector database handles semantic retrieval across unstructured documents and conversation history using advanced embedding models. The knowledge graph maps structured relationships between entities, policies, and procedures, ensuring factual consistency and logical leaps specific to your institution.
Tools
Pre-built connectors to 30+ essential enterprise systems including Salesforce, Epic, SAP, Microsoft 365, Zendesk, ServiceNow, Slack, and legacy mainframes via secure APIs. Each connector handles OAuth 2.0 authentication, rate limiting, payload validation, and exponential backoff error recovery automatically.
Skills
A composable library of agent capabilities: scheduling, form intake, escalation routing, document summarization, multilingual conversation, and compliance-checked drafting. Skills are modular, strictly typed, independently testable via unit tests, and combinable into multi-step Directed Acyclic Graphs (DAGs) for complex workflows.
Learning
The connective layer that ties the other four components into a single adaptive system. Governs the whole pipeline — what the agent learns, when, and how — ensuring continuous improvement safely inside a regulated environment.
Most AI agents are frozen the moment they ship. Vaiu agents are not.
Underneath every agent is a proprietary layer that governs the whole pipeline, not just the model. As it runs in production, it decides:
An agent is not one model; it is five components working together. Fine-tuning only the Brain leaves the other four static. This makes continuous learning safe:
QLoRA Fine-Tuning
Each domain brain is fine-tuned with QLoRA (Quantized Low-Rank Adaptation). By training only a small set of low-rank matrices while keeping base weights quantized, each brain learns a new vertical fast, on modest data, without drifting from its base knowledge.
FASTER TRAINING CYCLES
LOWER COMPUTE COST
LANGUAGES SUPPORTED
CATASTROPHIC FORGETTING
FULLY MANAGED INFRASTRUCTURE WITH AUTO-SCALING, LOAD BALANCING, AND 99.9% UPTIME SLA. SOC 2 TYPE II CERTIFIED ENVIRONMENTS WITH STRICT DATA ISOLATION. TECHNICAL SPECS AND DETAILED CONNECTIVITY REQUIREMENTS AVAILABLE UPON REQUEST.
RUNS INSIDE YOUR AWS, GCP, OR AZURE VIRTUAL PRIVATE CLOUD. YOUR NETWORK POLICIES APPLY. DATA NEVER LEAVES YOUR CLOUD ACCOUNT, ENSURING TOTAL DATA RESIDENCY COMPLIANCE FOR HEALTHCARE AND FINANCE VERTICALS. TECHNICAL SPECS TO BE SUPPLIED SEPARATELY.
COMPLETE AIR-GAPPED DEPLOYMENT BEHIND YOUR FIREWALL. FULL OFFLINE CAPABILITY ON YOUR OWN SECURE HARDWARE CLUSTERS. DESIGNED FOR GOVERNMENT AND DEFENSE APPLICATIONS REQUIRING ABSOLUTE SOVEREIGNTY.