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Linc AI
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Understand how work happens.Build AI that improves it.

Linc captures how your teams work, identifies where AI can improve business outcomes, and turns that knowledge into the context needed to build and improve internal agents.

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See how context is built ↓Backed by Y Combinator

Trusted by teams driving enterprise change

Ardurra
Marken
Rappi
Envision Cold
Duncan & Son Lines
Pacifica Logistics
EspriGas
McKim & Creed

From how work happens to context agents can use.

  1. 01

    Capture how work actually happens.

    Combine recordings, interviews, documents, and system logs to uncover decisions, exceptions, and handoffs.

  2. 02

    Identify improvements that matter.

    Compare opportunities against business goals such as lower handling time, fewer errors, and faster resolution.

  3. 03

    Give agents the context to succeed.

    Turn captured workflows into process specifications, instructions, and evaluation cases for your internal agents.

An example: invoice resolution

Redesign the work.
Build AI into it.

Automating a broken process scales its inefficiencies. Linc helps you rethink the workflow, then deploy agents that understand the decisions, exceptions, and systems behind it.

Governance by design. Define agent responsibilities, human approvals, and ownership as part of the workflow.

Explore the platform ↗
Across the systems
your business runs on.
SAPOracleWorkdayNetSuiteCoupaServiceNow

Lead the change.
From your side of the table.

Align the enterprise

Turn ambition into a plan.

Connect executive priorities to execution. Give business leaders and transformation teams a shared view of where to invest, who owns delivery, and what success looks like.

Evidence → Roadmap → Delivery
Discuss your transformation ↗

Better processes.
Agents that deliver.

Operational understanding becomes redesigned work, production agents, and outcomes you can measure.

Read customer stories
Global healthcare logistics

A triage agent built around the way service teams work.

More than 100 workflows captured. Routing decisions and ownership mapped. Operational context carried into a production AI agent.

Tickets auto-routed
50%
To first automation
2 weeks
Latin American superapp

Accounts payable, redesigned for AI from the start.

Fragmented process knowledge became a shared operating model. The future workflow was designed before automation was scaled.

Less manual entry
70%
Processing accuracy
98%

Make every deployment a learning loop.

Use measured results and real-world exceptions to refine the process, update agent context, and guide the next improvement—with people in control.

  1. Measure outcomes
  2. Refine the process
  3. Improve the agents

Enterprise control, built in.

Role-based access. Human approvals in workflow design. Audit trails for sensitive platform activity.

Private deployment options. Source lineage. Your data never trains a model.

Security & governance

A more intelligent enterprise
starts with understanding.

Start with the work that matters most to your business.

Let’s find your starting point