You tell us what recurring work is consuming your team. Lasso turns that job into a managed AI worker with role design, workflow placement, QA, monitoring, and escalation rules.
Workers connect to the tools you already use. They compile reports, monitor exceptions, draft communications, reconcile data, chase follow-ups, and prepare work for human review.
Your people stay in control. They review, approve, direct, and own the decisions. Lasso supplies the role architecture, managed operations, and improvement rhythm.
Clarify the recurring job, systems, cadence, outputs, review owner, and escalation path.
Build the role around your tools, business rules, data access, and approval boundaries.
Run the worker in a monitored environment before it touches production decisions.
Monitor performance, QA outputs, handle exceptions, and improve the worker over time.
Group related roles into Revenue Ops, Finance Ops, Customer Ops, Supply Chain, or Executive Ops pods.
Browse by industry or start with cross-industry roles. Every worker is designed around the job, systems, cadence, review path, and QA model. Related roles can become managed pods.
Tell us the function. We will scope the roles, review gates, monitoring, and operating rhythm.
30-minute call. We learn your operations, identify the roles you need filled, and scope the right AI workers.
A clear staffing plan: which workers, what they handle, what systems they connect to. You approve before we build.
We build, connect to your systems, and run in a controlled environment. Your team validates before go-live.
Workers go live. We monitor performance, handle issues, and improve them over time. Monthly reporting included.
A modeled deployment where AI workers monitor purchase orders against receipts, flag temperature and shelf-life exceptions, and generate daily review packets.
“Sample structure: order variance worker, shelf-life monitor, exception review queue, daily operating report.”
Modeled deploymentA modeled deployment where an Executive Operations Worker and Reporting Worker prepare weekly client briefings, internal status reports, and meeting context.
“Sample structure: meeting brief worker, reporting analyst, open-decision tracker, leadership review packet.”
Modeled deploymentA modeled deployment where workers pull project specs, assemble bid packages, compare pricing inputs, and prepare formatted proposals for review.
“Sample structure: spec extraction worker, bid package assembler, pricing QA, estimator approval queue.”
Modeled deploymentA modeled deployment where workers process intake forms, verify eligibility status, and coordinate scheduling exceptions across offices.
“Sample structure: document intake worker, eligibility checker, scheduling exception queue, human review path.”
Modeled deploymentTell us about the recurring work, systems, review level, and cadence. This produces a directional plan before a deeper design call.
Basic information helps us tailor the quote to your situation.
Estimate recoverable value, worker cost, net impact, and payback based on your department's recurring work.
Based on directional assumptions
Start with one role when the job is clear. Move into pods or a managed workforce program when the work spans a department.
For one defined recurring job with clear review and escalation rules.
For related roles across one operating function or department.
For organizations deploying AI workers across functions, locations, or business units.
Pricing follows the role, systems, risk, review model, and business value. The point is not a low-cost substitute for people; it is a managed operating layer for work that needs consistency, speed, and human judgment.
“Show the role, the systems it touches, the review gates, and the operating metric before we trust it.”
“Give leadership a clear read on recoverable value, operational risk, rollout effort, and who approves the output.”
“Start with one role, prove the cadence, then group related workers into a managed pod when the function is ready.”
Every worker ships with controls, audit trails, review gates, and escalation rules. Not experiments. Operating systems your team can stand behind.
The process is designed for leaders who run the work: business rules, handoffs, decisions, exceptions, and measurable output.
Every worker deployment follows a controlled process: assess, design, build, test, launch, monitor, improve.
Workers improve through monitoring, QA, feedback, and monthly operating rhythm instead of being left as unmanaged tools.
Lasso brings operators, builders, architects, and AI practitioners together around work that has to survive real operations.
One role can become a pod. A pod can become a department-level AI workforce program. Systems can absorb platform-scale complexity.
No. We handle all technical work. You focus on running the business. If you can describe what a process looks like today, we can build an AI worker to handle the repetitive parts.
No. AI workers handle the repetitive, time-consuming parts of your team's work. Your people keep decision authority, relationships, judgment, and exception handling.
Yes. Encrypted connections, role-based access controls, and audit logging are built into every worker. Managed deployments use isolated, secure infrastructure. Self-hosted runs entirely in your environment.
A focused worker pilot can usually be designed and tested in weeks. Department-level pods and enterprise workforce programs take longer because the review model, systems, and rollout need more design.
Most software your business already uses: Salesforce, HubSpot, Gmail, Outlook, Asana, Monday, Jira, QuickBooks, Xero, NetSuite, spreadsheets, databases, and more. We confirm compatibility during the design call.
That is usually the best path. Pick one recurring job, prove the operating model, then expand into a pod or broader managed workforce program when the work is ready.
Every worker has human checkpoints for critical decisions, confidence thresholds that flag ambiguous outputs, and monitoring that catches anomalies early. When issues arise, we fix them as part of the ongoing optimization.
Start with one role, a worker pod, or a managed workforce program. We will map the work, review gates, monitoring, and ROI case.