AI that understands your operations and acts on them, with you in control.
Humaneloom builds agentic AI systems that connect your knowledge, data, people and tools, then turn signals and conversations into verified, governed action. LoomOS runs the enterprise. FactoryOS runs the plant floor. Our engineers build the rest around how you actually work.
Discover → build → pilot within 2 weeks · Human approval on every consequential action
Work order drafted · Awaiting maintenance manager
WORKS WITH THE SYSTEMS YOU ALREADY RUN
Read-first connectors and MCP tools. Write access only where you approve it.
Two products. One shared core. Built around how you operate.
Start with a product, extend it with our engineers, or build a custom system on the same foundation. Every path shares the same memory, intelligence and controls.
LoomOS
The AI operating system for organisations
Turns meetings, documents, conversations and business systems into a living Company Brain, then coordinates specialised agents to get work done across teams.
FactoryOS
Industrial intelligence. Operational action.
Turns equipment signals, operational data and maintenance knowledge into prioritised decisions and governed actions, then checks that the fix worked.
The Shared Operating Core
Company memory
Records, documents, people and decisions with sources and access rules.
Right-sized intelligence
Fast models for routine checks, deep reasoning for hard cases.
Specialised agents
Each limited to its own tools, data and job.
Approval gates
People approve consequential actions, by policy.
Connectors and MCP
Read first, write later, through scoped access.
Audit and learning
Every step recorded; outcomes improve the next decision.
Your organisation finally has a memory.
LoomOS continuously turns meetings, documents, conversations and operational data into a living Company Brain, so every agent and every person works from the same up-to-date context.
LoomOS Company Brain
Continuous semantic context synthesis across conversations & data
The meeting ended. The work didn't.
A closed-loop execution cycle that turns conversational agreements into verified outcomes.
Capture
Approved meetings, chats and email are transcribed and cleaned.
Understand
Decisions, owners, deadlines and risks are extracted with sources.
Plan
The Supervisor picks the agents, tools and level of reasoning.
Approve
Consequential steps wait in a review queue for a person.
Act
Tickets, updates and messages are created in your tools, once.
Remember
Outcomes are verified and written back to the Company Brain.
Capture
Approved meetings, chats and email are transcribed and cleaned.
Understand
Decisions, owners, deadlines and risks are extracted with sources.
Plan
The Supervisor picks the agents, tools and level of reasoning.
Approve
Human GateConsequential steps wait in a review queue for a person.
Act
Tickets, updates and messages are created in your tools, once.
Remember
Outcomes are verified and written back to the Company Brain.
Industrial intelligence. Operational action.
Manufacturing generates a constant stream of signals. FactoryOS connects the right evidence, decides what matters now and coordinates the next step, without losing context between teams or systems.
Decision-to-action path
Prioritise
Risk weighted by equipment criticality.
Investigate
Telemetry, history, work orders and manuals in one evidence pack.
Recommend
Probable cause, uncertainty and next step.
Approve
A person signs off, by site policy.
Execute
Work order drafted or updated in your CMMS.
Verify
Recovery checked against expected operating state.
Prioritise
Risk weighted by equipment criticality.
Investigate
Telemetry, history, work orders and manuals in one evidence pack.
Recommend
Probable cause, uncertainty and next step.
Approve
Human GateA person signs off, by site policy.
Execute
Work order drafted or updated in your CMMS.
Verify
Recovery checked against expected operating state.
Built for high-reliability plant operations
Equipment intelligence and criticality
- One profile per asset
- Your criticality criteria, explained
- Recurring breakdown patterns
Risk signals and incident prioritisation
- A prioritised maintenance inbox
- Duplicates and noise separated out
- Context on why it matters
AI-assisted investigation
- Evidence organised around the incident
- Missing or conflicting data flagged
- Uncertain cases routed to people
Governed action and work coordination
- Existing work orders checked
- Approval and escalation rules
- Every action recorded
Verification and learning
- Post-repair checks against recovery criteria
- Reopens unresolved issues
- History that improves the next case
FactoryOS supports people and plant processes. It does not control PLCs or safety systems.
Where agentic AI pays off first.
The best first use case is a recurring problem with a clear owner, accessible data and a result you can measure. Here is where we usually start.
Breakdown and downtime response
When: A critical machine stops
What happens: Incident captured, impact assessed, evidence gathered, approved work coordinated, recovery verified
Predictive maintenance triage
When: Readings drift from normal
What happens: Risk ranked by criticality, root cause investigated, inspection prioritised
SOP and manual assistant
When: A technician needs the right procedure
What happens: Relevant passages from approved SOPs and manuals, with sources
Maintenance backlog prioritisation
When: The backlog outgrows the team
What happens: A/B/C criticality applied, duplicates removed, work ranked by impact
Quality and NCR follow-up
When: A non-conformance is raised
What happens: Evidence assembled, owner assigned, corrective action tracked to closure
Shift handover
When: A shift ends mid-incident
What happens: Open issues, decisions and next steps summarised for the next team
Not on the list? Most of our work starts with a workflow that isn't.
Tell us yoursOne technical foundation. Many industries.
Our core architecture adapts to high-consequence environments across manufacturing and knowledge-intensive enterprises.
Discrete manufacturing
Machining, fabrication, assembly and packaging lines.
Automotive and components
High-cost downtime, tight schedules, strict quality.
Process industries
Continuous operations where early warnings matter most.
Logistics and supply chain
Exceptions, supplier documents and coordination.
Enterprise shared services
IT, HR, finance and procurement operations.
SaaS and technology startups
Lean teams that need leverage, not headcount.
Working somewhere else? If fragmented information slows your work, we can likely help.
Talk to our engineersFrom your first agent to production.
For needs beyond our products, our engineers design and build agentic systems inside your environment: grounded in your data, wired into your stack and governed end to end.
Custom AI agents
Specialised agents for operations, engineering, procurement, finance, HR and support.
Agentic RAG and knowledge intelligence
Search and reasoning over your documents and data, with citations.
Workflow automation
Multi-step processes with assignment, exceptions, approvals and follow-up.
Industrial AI and decision support
Production visibility, maintenance workflows and technical-document intelligence.
System integration and modernisation
AI connected to ERP, CRM, MES, PLM, ticketing and collaboration tools.
AI engineering and implementation
Architecture, prototypes, evaluation, deployment and ongoing optimisation.
Discover, build and pilot within 2 weeks.
Discover
Map the workflow and agree one success metric before building.
Build
Connectors, knowledge, agents and guardrails, configured fast.
Pilot
A real team uses it, with trace reviews against the success bar.
Scale
Promote to production and extend to adjacent workflows.
Have an immediate operational bottleneck? Let’s map it.
Schedule a scoping workshopAutonomy where it helps. People where it counts.
Every agent runs inside your policies. You decide when it acts, when it recommends and when it hands off to a person.
Human approval gates
Consequential actions wait for the right person.
Least-privilege access
Role-based permissions for every agent, tool and dataset.
Full audit trail
Evidence, decisions, approvals and tool calls recorded.
Your data stays yours
Never used to train models.
Uncertainty handled openly
Missing or conflicting evidence is flagged and escalated.
Deploy where you need
Managed cloud, your own VPC, or on-premises and air-gapped.
Judged on outcomes, not on AI responses.
We measure your baseline first, agree how each metric is calculated, and review results with the team that owns the process.
On the plant floor
Operational impact tracked against telemetry & maintenance logs
Across the enterprise
Organizational agility measured across knowledge and execution cycles
We don't promise improvements in advance. Targets are set with you after the baseline is measured.
Toward general intelligence, one domain at a time.
We believe the practical path toward more general AI runs through deep, domain-specific intelligence: systems that understand one world, a factory or an enterprise, well enough to reason across all of it, act through its tools and learn from every outcome, while people stay in charge of what matters.
Grounded assistance
Answers from your own data, every claim linked to its source.
Specialist agents
Agents that investigate and recommend inside one bounded job.
Governed autonomy
Multi-agent workflows behind approval gates and a full audit trail.
Domain general intelligence
Our research direction: one system that understands a whole domain.
Levels 1–3 describe our products today and in delivery. Level 4 is our long-term research direction, not a current capability.
Map your first operating loop.
Bring one workflow that creates the most avoidable friction today. We'll define the baseline, the data and systems it needs, and a pilot with clear acceptance criteria.
Start with one workflow. Prove the value. Expand with confidence.