From contextual data foundation to autonomous agent teams — a complete operating system for the enterprise AI workforce.
Grid is how enterprises design, deploy, and operate agentic teams. Think of it as the HRIS for your AI workforce — you define roles, assign tools, set governance, and monitor performance across every agent in your organisation.
Agents don't operate in isolation. Grid orchestrates multi-agent teams that collaborate on complex workflows, with human-in-the-loop oversight at every critical decision point.
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.
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.
Design agents from enterprise context. Ingest your workflows and organisational data, get AI-matched team recommendations, then configure each agent's role, skills, data access, and autonomy.
Continuous monitoring, cost tracking, and retraining loops. Every agent action is logged, explainable, and reversible — meeting enterprise compliance from day one.
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.
Studio is how your teams interact with the intelligence layer day-to-day. Think enterprise search, knowledge retrieval, and conversational interfaces — all powered by your BCP and delivered through a governed, auditable experience.
While Grid manages the autonomous backend, Studio provides the human-facing interface where teams can query, explore, and action insights across the organisation's entire knowledge base.