The complete enterprise platform for designing, deploying, and operating AI agents — powered by your organisation's own context, knowledge, and workflows.
AI models don't understand your organisation's entities, workflows, financial logic, or regulatory constraints — so they hallucinate or produce generic outputs.
Siloed AI point solutions that can't collaborate, share knowledge, or reason across departments — creating fragmented intelligence.
No governance, monitoring, or orchestration for running AI agents in production — making it impossible to move from prototype to enterprise deployment.
AI models are commoditising. What doesn't commoditise is your enterprise's unique context — the entities, workflows, financial logic, regulatory constraints, and domain knowledge that make your business run.
BCP codifies all of this into a machine-readable ontology that every agent in your organisation consumes. It's the shared language that ensures agents reason consistently about your data without touching the underlying databases.
JENNA is the intelligence layer — the execution engine that powers agent reasoning, tool selection, and autonomous decision-making across your enterprise workflows.
Built on frontier LLMs with proprietary fine-tuning for enterprise contexts, JENNA bridges the gap between raw model capability and production-grade business outcomes. It consumes BCP context and executes through Grid's orchestration layer.
Agent Builder connects to your systems of record — ERP, CRM, communication tools, organisational charts, SOPs, and operational data. The Business Context Protocol ingests, structures, and contextualises this data into a machine-readable enterprise ontology.
This isn't a one-time import. BCP maintains a living understanding of your business that compounds over time, ensuring every agent operates with current institutional knowledge.
Based on your enterprise context, Agent Builder analyses workflow patterns, decision chains, and operational complexity to recommend the right agent team composition. Each agent is matched to a specific role with a confidence score.
The recommendation engine considers task dependencies, skill requirements, data access needs, and governance constraints — ensuring the team is production-ready from day one.
Configure each agent's role, primary task, core skills, and data access permissions. Set execution schedules, autonomy levels, and escalation thresholds — giving you granular control over how your AI workforce operates.
Every configuration decision is governed by your enterprise policies. Agents inherit RBAC constraints, audit requirements, and human-in-the-loop gates automatically from the BCP layer.
Grid is the runtime and orchestration layer for your AI workforce. Once agents are built, Grid deploys them into production — handling task execution, multi-agent coordination, and real-time monitoring across your entire organisation.
Think of Grid as the operating system for your AI workforce. It ensures agents collaborate on complex workflows with human-in-the-loop oversight at every critical decision point.
A live operational canvas showing your entire agentic workforce — which teams are active, what tasks are executing, where approvals are pending, and how data flows between agents.
Continuous monitoring, cost tracking, and retraining loops. Every agent action is logged, explainable, and reversible — meeting enterprise compliance from day one.
Calibrax Studio is the unified interface for your entire AI platform. BCP structures your data, JENNA powers the intelligence, Agent Builder designs your teams, and Grid runs them in production — Studio is where your people interact with all of it.
From enterprise search and knowledge retrieval to real-time agent insights and conversational AI — every capability flows through a single, governed experience built for the way teams actually work.