Signals into findings
Correlate alerts and webhooks into an operational record. Start investigating from the finding, without waiting for someone to open a ticket.
AUTOSOLVE · BY NOPAGER
AI-powered autonomous IT remediation.
AutoSolve diagnoses IT issues, reuses a proven resolution or prepares a new solution with AI, executes within your policies, and validates the result.
Works across your
operational world.
CLOSE THE LOOP
The same incident. The same manual checks. The same search for who fixed it last time.
AutoSolve brings that scattered work together: understand the problem, reuse a relevant resolution, or generate a new solution with AI when none matches. Prepare the action, apply your controls, and carry it through to a checked result.
Meet the full platformPUT IT THROUGH ITS PACES
Step through a matched resolution, a new AI-generated solution, or a missing prerequisite. See how the next decision changes.
FOLLOW THE WORK
Choose a scenario to see how the pieces connect. This walkthrough illustrates the workflow; it does not operate live systems.
Someone checks the host, finds the last ticket, repeats the fix, and writes the update.
One connected record from the original symptom to the verification result.
Gather the alert, target details, service state, and relevant prior resolution.
Build a proposed response with the intended target, prerequisites, and recovery checks.
Apply the configured policy. Route work requiring approval to an operator.
Run approved work, evaluate the declared checks, and retain the outcome.
THE CONNECTED PLATFORM
Seven connected areas carry context from the first signal to the next visit. Explore the depth behind each one.
Bring signals, system evidence, and previous resolutions into the same investigation.
Correlate alerts and webhooks into an operational record. Start investigating from the finding, without waiting for someone to open a ticket.
Inspect the likely cause, confidence, supporting evidence, and missing information before reviewing a proposed fix.
Gather process, service, resource, installation, and event-log context. Resolve application names against the affected system.
Review repeated log signatures, telemetry anomalies, and incident history to identify work worth automating.
Turn operational know-how into workflows your team can inspect, schedule, and reuse.
Describe an operation and prepare an editable automation. Review its proposed steps, inputs, runtime, and target before saving.
Run work on demand, on a recurring schedule, from a matching event, or through a signed webhook.
Create, edit, enable, pause, and trigger automations. Keep run status and approval requirements visible.
Update incidents, add work notes, create issues, transition tickets, and update knowledge pages through connected tools, including ServiceNow.
Match the proposed work to a viable execution path, then separate a completed action from a verified recovery.
When no existing solution matches, AI uses the problem, target context, and available evidence to generate and prepare a new solution. The proposed work then goes through validation, applicable approval policy, and execution-readiness checks.
Validate the target, tools, runtime, permissions, and scope. If a prerequisite is missing, surface it before dispatch.
Execution paths include agents, SSH, WinRM, cloud command services, containers, and databases. Availability depends on the task and configured access.
Check service, process, port, HTTP, file, database, and container state. Use declared rollback steps where the selected action supports them.
Put the history your team already owns to work, with the source and outcome still attached.
Import historical resolutions and operational records from configured sources or JSON/CSV. Retain their origin for review.
Find exact and similar past issues within the customer context. Give the planner relevant precedents.
Record whether a fix was verified, edited, rated, or rolled back. Use those outcomes to improve reuse and ranking.
Manage source sync, corpus health, and curated model-evaluation or fine-tuning exports with tenant scoping and sanitization.
Bring inventory, remote work, readiness, and configured notifications into one operating view.
Inspect inventory and heartbeats, distinguish online and offline systems, and organize endpoints with tags.
Track queued, claimed, completed, and failed work. Review coverage and preflight gaps before a rollout.
Use configured cloud inventory, identity, and device-management connections, with permissions scoped to the relevant actions.
Configured Slack, Teams, and email notifications connect approval requests, completions, failures, and rollbacks to their run records.
Make proposed work, human decisions, and execution evidence available to the people responsible.
Apply capability rules, role permissions, and risk-based review. Keep approval decisions attached to the run.
Use dry runs, maintenance controls, and an emergency stop. Validate proposed work and its signed execution context.
Inspect approvals, execution outcomes, verification, and audit events. Find failed, stuck, or incomplete work.
Manage memberships, identity mappings, connectors, secret controls, and policies for the selected deployment.
Carry useful context across visits, from host diagnostics to a record of what changed.
Use local field mode for host diagnostics, findings, and remediation review during a customer visit.
Inspect available host, peripheral, and network context within the connected environment and your permissions.
Save a site baseline and identify added, removed, and changed software in a later snapshot.
Keep local visit and audit records alongside findings and runs. Cloud services and AI generation still require connectivity.
All published capability areas have been internally verified, as confirmed by founder Dakota Vogt. Onboarding connects your systems, sets access and policies, and defines your acceptance criteria.
INSIDE THE APPLICATION
Real application views, from designing an automation to inspecting a run. Screenshots show the application interface and test-environment data.
BUILT AROUND YOUR WORK
Start where the repeat work is most visible. Connect incident response, automation, knowledge, and field work around the needs of your team.
Connect investigation, operational knowledge, approvals, execution, and verification in a single workflow.
Explore the workflow 02 / MANAGED SERVICE PROVIDERSGive technicians a shared path from a familiar customer problem to a reviewed, reusable response.
Explore the workflow 03 / FIELD SERVICE TEAMSBring diagnostics, site baselines, remediation review, and visit history into a portable workflow.
Explore the workflowWORKING CAPABILITIES. VERIFIED WORKFLOWS.
Automation, agent workflows, ServiceNow, and the other published capabilities have been internally verified. See how the working platform connects the steps your team handles today.
See the evidence and its scopeSelected records: July–August 2026. Full capability verification confirmed by founder Dakota Vogt on September 30, 2026.
A FEW GOOD QUESTIONS
NoPager is the company behind AutoSolve. Our mission is fewer avoidable interruptions for the people who keep IT running. AutoSolve connects diagnosis, remediation, and validation so teams can resolve work within their defined operating policies.
AutoSolve is NoPager’s AI-powered autonomous IT remediation platform, built by founder Dakota Vogt. It connects investigation, AI solution generation, workflow design, knowledge reuse, execution, verification, fleet management, governance, and field service. Existing application screenshots may show the AutoSolve name.
AI generates and prepares a new solution using the problem details, target context, and available evidence. The proposed work is validated and checked against execution requirements and the configured approval policy before it runs. The result is then checked, and outcome feedback can inform future reuse.
Execution follows the configured policy and access. You can begin with planning, read-only diagnostics, and dry runs. The pilot defines which actions can execute and which need an operator’s approval.
Yes. The platform includes configured source ingestion, ticket and knowledge actions, cloud and endpoint paths, and historical-resolution imports. We check the specific integration and permissions required for your workflow before committing to scope.
Pilots and commercial deployments are scoped individually around the workflow, environment, integrations, onboarding, and support required. You receive a written scope and quote before any paid engagement.
The current buying path is a founder-led demonstration and a scoped, supervised pilot. There is no public self-service subscription or instant production activation on this website.
Founder Dakota Vogt confirms that all published capabilities have been verified, including automation, agent workflows, and ServiceNow. The evidence page includes that confirmation alongside selected application and live-cloud test records. Customer onboarding establishes the connections and controls for your environment.
LET’S MAKE IT WORK
See the platform. Choose a workflow. Define what success looks like.