Why is checkout latency spiking in production?
Private preview · Requests open
Incidents leave a trail.
Lino follows the evidence.
A self-hosted AI investigation partner that works inside Slack, gathers bounded read-only evidence from AWS and GitHub, and explains what it found — claim by claim.
Self-hosted · Read-only · Evidence-grounded
Every conclusion stays connected to its source.
01 Read-only by construction
02 Evidence before inference
03 Self-hosted in your AWS account
04 Explicit gaps and confidence
Most AI answers ask you to trust the model.
Lino asks you to inspect the evidence.
Observe
Collect a bounded window of logs, runtime metadata, and relevant code changes.
Correlate
Let specialized agents compare signals without gaining permission to change your systems.
Verify
Review every material claim against stable evidence IDs before the report reaches Slack.
A calm second pair of eyes, right where the incident starts.
Choose a question to preview how Lino separates observation, inference, and uncertainty.
One question.
Five bounded stages.
Deterministic code controls identity, scope, limits, and rendering. Agents reason only inside those boundaries.
Resolve
Identify the exact app, account, region, and allowed evidence window.
Collect
Read redacted evidence from CloudWatch, Lambda or ECS, and GitHub.
Investigate
Send only relevant, bounded context to specialized agents running in parallel.
Review
Challenge unsupported conclusions, contradictions, and missing evidence.
Report
Return a cited explanation, explicit gaps, and one practical human next step.
No floating conclusions.
Every observation points to evidence. Every inference names its support. Every hypothesis is visibly labeled — and collection failures stay visible as gaps.
- 01 Stable evidence IDs
- 02 Claim-level citations
- 03 Explicit contradictions
- 04 Calibrated confidence
Small control plane.
Strict trust boundary.
Lino lives in your AWS account and assumes temporary, read-only roles in explicitly configured target accounts.
Read-only by construction. Lino has no customer-system mutation tools. Denied access fails closed and becomes an evidence gap — never an invented fact.
Bounded access
Allowlisted accounts, regions, applications, resources, and evidence windows.
Visible failure
Denied, missing, timed-out, and truncated evidence stays visible in the report.
Recoverable runs
Idempotency, leases, checkpoints, cancellation, bounded retries, and a DLQ.
Questions worth answering before you trust an incident agent.
Clear boundaries are a product feature, not fine print.
01 Is Lino available for private preview?
Requests are open while Lino completes its first-release gates: reproducible deployment, failure testing, evaluation, security review, and a synthetic demonstration. Preview access will be matched to teams whose incident workflows fit the current product scope.
02 Can Lino change production systems?
No. The product boundary is read-only. Lino collects evidence from explicitly allowed operational sources, then returns a cited report and one human next step.
03 Where does operational data go?
The control plane is self-hosted in your AWS account. Evidence is bounded and redacted before model context. The configured model provider is an explicit data-processing choice and invalid provider configuration fails closed.
04 What will the first release investigate?
The first release focuses on CloudWatch Logs, Lambda and ECS runtime metadata, and GitHub deployment context, all operated through Slack direct messages and @Lino mentions.
05 How do I request access?
Use the private-preview form below and tell us which incident workflow you want Lino to investigate. We will use that context to evaluate fit and follow up directly.
Private preview · Requests open
Bring your hardest incident.
Tell us where investigations slow down today. We are inviting a small number of cloud-native teams to help shape a careful, evidence-grounded release.
- 01 Self-hosted in your AWS account
- 02 Read-only operational access
- 03 Human decisions stay in control