Interloom

What Interloom does

Interloom is the first Navigation System for Work that helps map how teams actually work. It guides operational teams with suggested next steps and relevant context, empowering AI agents to follow their lead. The platform enables delegation of workstreams from shared inboxes, ticketing systems, and operational systems of record, ensuring teams and agents never drop the ball. It remembers every resolution and learns through its context graph, bringing domain experts and AI agents into a collaborative operational surface. Interloom orchestrates work based on precedent, finding the best matching prior cases, building language-based procedures for high-load workstreams, and routing tasks to the right expert, agent, or integration. It learns from every successful case outcome, constantly improving how operations are navigated, much like Google Maps for work. The system is designed to align with the value delivered, with pricing based on AI agent interactions rather than headcount, offering unlimited users and workspaces. It supports various deployment models including SaaS, Private VPC, and Private VPC with Bring Your Own Model, all with enterprise-grade security and compliance. Interloom aims to rewrite organizational theory by creating a future where humans and AI agents work together seamlessly, unlocking a 10x increase in productivity.

Products

• Interloom PlatformA navigation system for work that orchestrates human teams and AI agents. It delegates workstreams, learns from resolutions via a context graph, and guides operational teams with suggested next steps and context. It finds the best path through every case by orchestrating work based on precedent, building language-based procedures, and routing tasks to the right worker.
• MemoryRankA learning algorithm for operational work that constantly improves how Interloom navigates operations. It learns from each resolved case, like Google Maps for operations, by grading outcomes, remembering the path, and routing better next time. It surfaces the closest successful cases with relevant people, agents, documents, and decisions.
• Interloom AssistantA conversational interface that allows operators to steer the system in natural language, design workflows, line up agents, plug in tools, and steer costs. It enables automation through natural language descriptions.
• Field AgentsAutonomous workers within Interloom that carry out operations. They run autonomously with narrow scopes and credentials, pulling from memory of previous work, completing tasks, and producing artifacts. They raise their hand and pull in domain experts when work falls outside their scope.
• Cloud AgentsAgents that run in the cloud on Interloom's compute, with their own credentials and session. They operate always-on, handling cases, procedures, or questions without requiring the user's device to be active.
• Context GraphA semantic memory layer that transforms raw workflows into codified operational context. It grounds agents and experts in verified precedent, structured relationships, and collective intelligence. It resolves operational entities into first-class objects with stable identities and typed semantic relationships, providing a precisely scoped, token-efficient context window for every agent invocation.

Key capabilities

• Delegate workstreams from shared inboxes, ticketing systems, and operational systems of record
• One Collaborative Workspace for domain experts and AI agents
• Workspace that learns through a context graph
• Triages, assigns, follows up, and escalates across people, agents, and systems
• Orchestrates work based on precedent
• MemoryRank for learning and improving operational navigation
• Integrations with existing tools (SharePoint, Salesforce, SAP, Microsoft Teams, Confluence, Google Workspace, ServiceNow, Jira Service Management)
• Usage-aligned pricing based on agent interactions
• No seat-based pricing, unlimited users, cases, and workspaces
• Predictable and transparent pricing with fixed per-interaction rates and prepaid volume discounts
• Self-service budget controls per space, team, or use case
• Multiple deployment models: Interloom SaaS, Private VPC, Private VPC with Bring Your Own Model
• Enterprise SSO, SLA and Enterprise Support, Developer Tooling and Agent Tools, Enterprise Security and Compliance
• Steerable system in plain language via Interloom Assistant
• Clear accountability for agents with owners, roles, and reporting lines
• Role-based access for agents
• Operational leadership feedback and approval in natural language
• Describe to Automate: natural language construction of procedures and agent briefings
• Cases as discrete units of work with status, history, files, and human/agent threads
• Procedures: sequence of stages with instructions, written in plain language with deterministic scripts/tools
• Human hand-offs as first-class stages in procedures
• Model Agnostic: pick any top models from frontier labs, switch based on cost-quality tradeoff
• Cloud Agents for always-on, autonomous work
• Scheduled Tasks
• Case-resolution system orchestrating agents, experts, and integrations
• Context Graph for codified operational context
• Memory Layer decoupling meaning from storage
• Precedent Discovery via Triangulation
• Cold-Start Corporate Memory by pre-processing existing data
• Grounding that agents can cite with specific object and relationship references
• Cited Outputs for agent actions
• Single Source of Truth via canonical layer
• Enterprise Governance with granular permissions over nodes and relationships
• Structured Articles for shared knowledge between humans and agents

Use cases

• Delegate workstreams from shared inboxes
• Delegate workstreams from ticketing systems
• Delegate workstreams from operational systems of record
• Customer support
• Logistics operations
• Claims processing
• Insurance claims resolution
• Freight & Delivery Coordination in logistics
• Compliance & Transaction Cases in banking (KYC reviews, wire approvals, fraud alerts)
• Service Desk Resolution in ITSM (access requests, outages, change approvals)
• Billing & Outage Cases in energy (meter faults, billing disputes, outage reports)
• Automate routine tasks
• Design and continuously improve workflows
• Operational orchestration
• Resolving complex cases requiring human judgment and AI assistance

AI approach

Interloom provides a 'Navigation System for Work' that orchestrates operational workflows using AI agents, experts, and integrations. It learns from every resolution, building a 'context graph' and using a 'MemoryRank' algorithm to find the best path through cases, build procedures, and match the right worker. The system is model agnostic, allowing users to choose and switch between top models from frontier labs based on cost-quality tradeoffs. It emphasizes natural language interaction for designing workflows and briefing agents.

Tech named: large language models, vector embeddings, process traces, adaptive knowledge graph, MemoryRank, Azure Kubernetes Service (AKS)

Industries served

• Insurance
• Logistics
• Banking
• IT
• Energy
• Facilities

What it says sets it apart

• First Navigation System for Work
• Maps how teams actually work and guides with suggested next steps and context
• Empowers AI agents to follow human lead
• Learns through a context graph from every resolution
• Orchestrates work based on precedent, finding best matching prior cases
• Builds language-based procedures for high-load workstreams
• Routes tasks to the right expert, agent, or integration
• MemoryRank algorithm constantly improves navigation like Google Maps for operations
• Pricing aligns with value delivered, rewarding automation not headcount (usage-aligned, no seat-based pricing)
• Unlimited users, cases, and workspaces in every plan
• Model agnostic, allowing choice and switching of top models based on cost-quality tradeoff
• Cloud Agents provide always-on, autonomous work without user interaction
• Case-resolution system that brings together agents, experts, and technologies
• Does not optimize for just one layer (AI workers, data models, customer conversations) but routes to the best combination
• Context Graph transforms raw workflows into a semantic memory layer for verified precedent and collective intelligence
• Cold-starts corporate memory by pre-processing existing data
• Agents provide cited outputs, linking actions back to knowledge and precedent
• Single Source of Truth via canonical layer for all agents, dashboards, and workflows
• Enterprise Governance with granular permissions over knowledge
• Rewriting centuries of organizational theory for seamless human-AI collaboration

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.