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    SELF-IMPROVING AI COWORKERS

    Give AI a job, not just a prompt.

    Give one recurring job to an AI coworker. It picks up the pending work across your tools, does it, and hands back a finished outcome for a person to approve.

    Less manual workload. More time for customers, decisions and growth.
    • A model for each team
    • Data never leaves your VPC
    • Knows how the team operates
    Book a Working Session See how coworkers work
    Backed byEntrepreneurs First
    AdaSite Reliability Engineer
    Waiting
    Checkout is failing for an enterprise customer.Zendesk · 03:07 AM · $180k account
    Working
    1. Read the ticket and the error spike
    2. Traced it to deploy 8b21
    3. Checked the payments runbook
    Done

    Incident brief written, rollback prepared.

    ENG-731 raised with an owner. Customer update drafted.Ready in 6 min · Maya approves the production change

    Linkence integrations

    Explore coworkers by role
    View all eight roles
    SITE RELIABILITY ENGINEER · ENGINEERING

    Own incident recovery without pulling the sprint off the code.

    Engineering leads lose hours reconstructing incidents across Datadog, Jira, GitHub and runbooks. Hire the role that owns that loop.

    OWNS INCIDENT RESPONSE

    It cuts incident recovery time and takes investigation, tickets and follow-ups off the sprint.

    • Assembles incident context from Datadog, Jira, GitHub and the runbook
    • Matches known issues before a duplicate ticket is opened
    • Drafts the Jira ticket and the follow-up pull request with citations
    • Escalates to the on-call engineer only when a decision is required
    See the Engineering role
    Datadog6Jira4GitHub3Confluence2
    TODAY 09:14 · PAYMENTS-API · PR OPENED

    5xx spike on payments-api Monitor · Detected 09:14

    Checkout failing after a declined card ENG-731 · 4 new tickets today

    Retry backoff missing in the 09:11 release payments-api · last deploy

    Card retries looping with no timeout Incident notes · 09:20

    WORK MOVINGPR opened

    ✓Ticket opened
    ✓Alert closed
    ✓On-call not paged
    WHY AI COWORKERS

    Your employees lose hours every day to repetitive digital work.

    Up to 70% of employee time is spent on repetitive tasks that can be automated, from training and reporting to coordination and routine follow-ups.

    AN AI COWORKER GIVES LEADERS
    • Blockers and overdue commitments from connected systems
    • What changed since the last update
    • Decisions that need an owner
    • Conflicting information flagged before it spreads
    • Recommended next steps ready for approval
    • A source link for every important claim
    See how AI coworkers work
    Jira12Slack8Gmail3GitHub2Drive2
    MON 08:30 · COMPANY ACTIVITY · PRIORITIES READY

    Security review is blocking the payment migration OPS-184 · Owner: Nisha

    Client sign-off on the timeline is 2 days overdue Client thread · Owner: Maya

    Tokenisation exception needs a leadership decision #atlas-delivery · Raised today

    Migration window approved for 18 to 22 August Changed since last review

    WORK MOVINGNext steps ready

    ✓Blockers surfaced
    ✓Decisions routed
    ✓Follow-ups ready
    NOT A GENERIC MODEL

    Each coworker, on each dedicated team, gets a customized model.

    Trained to your use case and how that team works, then self-improving from day one. Data never leaves your VPC.

    >20×

    faster response on the recurring job than a general-purpose model that has to re-learn the playbook on every run.

    70%

    reduction in token cost and usage. High ROI on each token spent, because the team model already carries the skill.

    Per coworker

    Each coworker on each dedicated team gets a customized model, trained to your use case and how they work.

    Human owner AI co-worker

    Click any AI co-worker to inspect its role

    CEO
    CPO
    CTO
    COO
    People Operations Lead
    Employee Experience Lead
    Director of Workplace Systems
    Delivery Operations Lead
    Revenue Operations Lead
    Finance Operations Lead
    Enterprise Security Lead
    Identity Architect

    Swipe to explore the full workforce map →

    FROM REPETITIVE WORK TO COMPLETED WORK

    Don't spend hours turning scattered information into a finished outcome.

    AI Coworkers that own job roles, not just tasks

    See how AI coworkers work
    01 · HIRE A COWORKER

    Describe the job in plain language. That is the setup.

    Design and deploy AI Coworkers that handle work end-to-end, from IT operations to enterprise support. Each AI Coworker comes with its own role, skills, and access controls. Acts just like a team member.

    • Plain-language responsibility, no flowcharts to build
    • Connects to Jira, Slack, Sentry, Gmail, GitHub and more
    • Hands work to other approved coworkers when the job spans roles
    • Guardrails and escalation to a human, built into the job
    02 · RUN THE WORK

    It starts the work. You review what it did.

    The coworker picks up the job on its own. Each tool lands on a timeline you can audit, with a tick when it succeeds. Open thinking to see why it acted, or open a step to see the exact call.

    03 · SELF-IMPROVING

    The longer it works, the better it works.

    A Linkence coworker improves itself with every task it completes. It sharpens how it writes, decides and acts for your team, while generic AI tools stay exactly the same. No retraining, no prompt tuning, no rebuilding.

    • Better outcomes every week, from real work
    • Every improvement is visible and under your control
    • Nothing changes without your approval

    WEEK 2: Writes updates in your team's voice

    Continue in
    Slack
    Discord
    Desktop
    Widget
    Web application
    ENGINEERING OUTCOMES

    What changes for engineering.

    The large number is after Linkence. The line underneath is the same metric before.

    After Linkence

    5min

    Incident detection time

    Time to detect a production incident.

    Before Linkence: a few hours
    After Linkence

    80%

    Incidents handled without paging on-call

    Known issues investigated, ticketed and drafted without pulling an engineer off the sprint.

    Before Linkence: 15%
    After Linkence

    0repeats

    Repeat incidents

    Incidents caused by a previously known problem.

    Before Linkence: 4 of 18
    After Linkence

    11min

    PR cycle time

    Time from the fix ticket to a drafted pull request.

    Before Linkence: 2.5 days
    EVIDENCE AT EVERY STEP

    The knowledge backbone for governed work.

    Every answer stays connected to its sources, controls and public proof.

    1100+ ready integrations. Each colour family represents a connected source class: communication, documents, delivery, code and internal systems.

    CUSTOMER STORIES

    Built around the way real teams operate.

    See how teams use Linkence inside the systems they already trust, with the operating process and control boundary made explicit.

    01EkayanConsultancy · Client operations

    Grounded client replies, with judgment preserved.

    Client email replies are prepared from Ekayan’s own knowledge. Sensitive or ambiguous messages return to a person before anything is sent.

    Read the story
    02MICROSIGNManufacturing · Microsoft 365

    One operating layer across the Microsoft workspace.

    Outlook, Teams, OneDrive and SharePoint work together to organise day-to-day schedules, retrieve the right context and keep recurring work moving.

    Read the story
    01

    Linkence from

    Use Linkence from Slack, Discord, Chrome, desktop, widget or MCP.

    Explore Linkence Everywhere Bots · desktop · widget · MCP
    02

    A model for each team

    Train a dedicated model on how that team operates, or bring approved providers and customer-managed keys. Isolated per tenant, including VPC for enterprise engagements.

    Explore model providers Team models · tenant VPC · 15 inference providers
    03
    { API }

    Custom systems

    Connect internal ERPs, CRMs, SQL sources and applications after technical review.

    REST · SQL · custom adapters
    AI COWORKER QUESTIONS

    Direct answers before the first conversation.

    Start with one team and one recurring job. Engineering, HR, Sales, Support, Operations, Finance, Product, and Marketing can each begin with a clearly owned responsibility.

    What is an AI coworker?+

    A Linkence AI coworker is a digital employee for one recurring job. You give it a name, a role and a written responsibility, connect the apps it may use, and set the guardrails and who it should escalate to. It then runs the work and returns an outcome you can review.

    Where should we start?+

    Choose the department carrying the repeated coordination, backlog, or missed follow-through, then choose one responsibility with a visible output. Bring that job and its owner to the working session. We hire the coworker against the job, not against a generic department demo.

    What systems can a coworker use?+

    Each coworker connects only to the apps you turn on for that job, such as Jira, Slack, Sentry, Gmail and GitHub. It works inside the permissions of its owner and cannot open information that person cannot access.

    How does a coworker improve over time?+

    Every Linkence coworker is self-improving. It learns from the outcome of every task and from how your team responds to its work, then applies those improvements to future runs. Improvements are described in plain language your team can review, and nothing changes how the coworker works without your approval.

    What happens in the working session?+

    We take one team's recurring work, write the responsibility in plain language, connect the apps it needs and run the coworker once so you can see the outcome, the timeline and where a human still steps in. Production access is not required for the first session.

    Are customized models available for each engineering team, without data leakage?+

    Yes. Each coworker on each dedicated team gets a customized model, trained to that team's use case and how they work. Payments does not train Platform. Platform does not train Support. Training and inference stay inside the tenant boundary, including customer VPC where the engagement requires it. Specialized team models respond more than 20× faster, with a 70% reduction in token cost and usage, so each token spent has a higher return.

    AN OUTCOME, NOT A DISCOVERY CALL

    Bring one recurring job. See the coworker Linkence hires.

    Bring the trigger, systems, finished output, metric, and human owner. We will configure the coworker's tools and boundaries, then run the job so you can review the work.

    Book a Working Session