OLOperating Leverage

What we build

AI systems shaped around the work teams already need to move.

Every engagement starts with a workflow that is slow, repetitive, high-risk, or blocked by missing context. The model, retrieval, tools, approvals, and integrations follow from what the work needs to change.

AI Support Triage Agent

For companies with high-volume support and operations queues.

Turns messy inbound queues into ranked, owner-ready work with context attached.

Reads from

  • Support tickets and queue metadata
  • Help center, SOPs, and policy docs
  • CRM and account context
  • Escalation rules and service targets

Produces

  • Priority and owner recommendation
  • Suggested reply or next action
  • Escalation path with supporting context

What changes

Lower triage time, faster first response, and fewer handoffs without blind automation.

Internal Knowledge Brain

For teams with scattered docs, Slack decisions, SOPs, and customer context.

Makes operating knowledge usable in the moment instead of buried across tools.

Reads from

  • Docs, wikis, and SOPs
  • Slack decisions and meeting notes
  • Customer-specific context
  • Policy and process documents

Produces

  • Cited answers with source links
  • Recommended next step or owner
  • A traceable record of what was used

What changes

Less time hunting for answers, more consistency in decisions, and fewer context-switches across tools.

Engineering Backlog Agent

For product and engineering teams under constant delivery pressure.

Removes engineering drag around investigation, drafting, and review preparation.

Reads from

  • Issue tracker and backlog context
  • Repository code and docs
  • Runbooks, incidents, and prior changes
  • Tests, logs, and CI output

Produces

  • Investigation summary and likely root cause
  • PR draft or code-change starting point
  • Review artifacts and rollout notes

What changes

Faster bug investigation, cleaner handoffs, and more engineering time spent on the work that actually needs judgment.

01

Knowledge and decision workflows

For companies where critical work depends on finding the right policy, precedent, customer detail, or operating rule.

Internal wiki and SOP assistant
Sales and support enablement brain
Policy-aware Q&A with source provenance
Decision memo drafting from company context

02

Operations and process agents

For high-volume work that crosses queues, tools, teams, and approvals.

Ticket triage and routing
Document intake and reconciliation
Approval workflow copilots
Customer operations automation

03

Engineering and product agents

For teams that want AI to remove engineering drag without giving up control of production.

Background PR agents
Bug and incident investigation
Release note and migration drafting
Product analytics investigation

04

Analytics and reporting agents

For leaders who need answers, tables, charts, and narratives without waiting on one overloaded analyst.

Metric explanation agents
Dashboard generation
Weekly business review drafts
Anomaly investigation and commentary

05

AI infrastructure and governance

For teams that need the architecture beneath AI workflows to be secure, measurable, and operable.

Sandboxed execution environments
Model routing by task and risk
Evaluation harnesses
Audit trails and approval gates

Operating layer

What we put around the workflow so it can survive production.

The workflow is the entry point. The operating layer is what keeps it useful, measurable, and safe once teams rely on it.

01

Workflow discovery

Map where teams lose time, money, and judgment across docs, tickets, approvals, code, support queues, and operational handoffs.

02

Agent systems

Design agents that can investigate, draft, route, reconcile, build, and ask for human input when the decision carries risk.

03

Company brain

Turn scattered knowledge into permission-aware context: policies, SOPs, customer facts, runbooks, product decisions, and institutional memory.

04

Governance layer

Add the controls that make production AI survivable: sandboxes, model routing, evals, audit trails, approval gates, and observability.

Start small, build seriously

Bring your most expensive workflow. Leave the call with a ranked plan for where AI pays off first.

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