Polylane

Polylane is a platform that makes your software self-operating. Its AI agents read your code, watch your infrastructure, and fix production issues for you, automatically. Polylane connects your code, your infrastructure and your observability data, investigates every incident it detects, and opens a pull request containing the fix. When a problem cannot be fixed in code, Polylane still gives you the root cause and a recommendation. It is built for engineering teams that run production software and want to stop being on call, and it works with the providers, databases, repositories and tools a team already runs, with no migration and no new SDKs. The premise behind the product is stated plainly on the site: "Nobody should be on-call." Polylane was built by engineers who carried the pager, from Cloudflare, Webflow, Groq, Twilio, Uber, and Robinhood. Founder Boris Tane, who spent years building observability platforms at Baselime and then at Cloudflare, describes the gap directly: "Our tooling is still terrible at finding what's broken, and it can't fix anything on its own. On-call is still broken. I'm fixing it." The problem Polylane addresses is that observability stacks surface symptoms — monitors, dashboards and alerts — but leave the investigation, the diagnosis and the repair to a human who has to be awake to do it. Polylane is designed to close that loop: detect the issue, work out what caused it, and produce the fix. Detection is handled by agents that read your metrics, logs and traces on a cadence and judge them against how each resource normally behaves. Anything your team already charts becomes a check, so existing monitoring investments feed directly into Polylane's analysis. The site illustrates this with a real scenario: Polylane re-detected an issue on checkout-edge when the same fingerprint fired again, quiet for six days since its last resolution, and recorded 118 occurrences arriving from a single Datadog monitor. Rather than treating 118 alert firings as 118 separate problems, Polylane consolidated them into one issue, which is how it keeps incident noise from turning into pages. From there, Polylane drives from issue to fix. It triaged the checkout-edge problem as an incident at 02:14, noting 18x P99 latency against its own baseline, sustained for 12 minutes and off its hour-of-week band. It then started the fix run: one agent going from the evidence to the pull request, which it opened at 02:19 under the title "Restore Hyperdrive pool size in checkout-edge," against coreplane/checkout-edge#142 with critical severity and CI passing. The pull request carries the full context of the investigation — files changed, an investigation view, a timeline, properties, and a unified or side-by-side diff of the TypeScript source — so a reviewer sees the reasoning, not just the patch. That example directly reflects the product's promise: AI agents that fix production before you wake up. Polylane also prevents slop from hitting production. All code changes, from bots and engineers alike, get reviewed against live telemetry. In the example shown on the site, a developer opens a pull request titled "Add trigram index for order search #482." The Polylane bot comments with a caution that merging may degrade production with high impact, explaining that the migration adds a CREATE INDEX statement without CONCURRENTLY, that a plain CREATE INDEX takes a full write lock on the orders table for the whole build, and that checkout sustains roughly 38 writes per second on that table, with every one of those writes queuing behind the lock. It recommends building the index with CREATE INDEX CONCURRENTLY outside the transactional migration, and the merge is blocked. This is production-impact review grounded in real traffic data rather than static analysis alone. Underneath these workflows is a context graph that fully maps your app, from cloud to code: all services, repos and providers in one place that powers everything else. The topology view lets you search your cloud resources and filter them, switch between Galaxy, Flow and Table presentations, and see issue hotspots and change hotspots per resource. Clicking a dot opens the resource, and holding traces its blast radius. Resources are annotated with their importance — a Cloudflare Worker named checkout-edge marked critical to your architecture, with four issues and twelve changes in the last seven days; a Cloudflare Hyperdrive instance with seven changes in the last seven days; an AWS Lambda function marked standard with two issues; and a PlanetScale database marked critical with one issue and three changes — and you can ask questions about your topology in natural language. Polylane is also always available to answer questions on call. It knows your app and will dig through data for you. In the Slack example shown, an engineer asks in the engineering channel whether checkout feeling slow is them or payments-api. PolylaneAgent answers that it is them, that checkout-edge wall time P99 is 18x its own baseline, that requests are queuing for a Hyperdrive connection rather than on a downstream call, that payments-api is answering in 180ms and has been flat for a week, and that deploy 9f3c2a1 at 2:02 AM shrank the hd-prod pool from 50 connections to 5. Asked how long it has been queueing, it answers nine minutes, since the deploy landed, notes it never went above 2 before that, and reports that it submitted a PR fix and tagged a colleague to deploy two minutes ago, with a pool queue depth chart attached. It shares insights with other agents as well, acting as a production context layer for your coding agents over MCP or the CLI. In the example, a developer asks Claude to make region a required field on the checkout request schema. The coding agent calls Polylane to search callers of POST /checkout and to query logs for request shapes, then reports that cart-svc and edge-gateway still send region-less requests — 41,200 in the last 24 hours — so requiring the field now would return 400s to both, and suggests defaulting it, migrating the two callers, then requiring it. The developer is offered a choice of plans rather than an unreviewed edit. Control stays with the team. Polylane does not change production without review: every write pauses for your approval with the exact request on screen, and code changes arrive as pull requests that your review and your CI gate. That combination — autonomous investigation and fix generation, with human approval and existing CI as the gate — is how the product keeps automation accountable in environments where a wrong change is expensive. Polylane integrates with AWS, Cloudflare, Vercel, Fly.io, Render, Kubernetes, PlanetScale, Railway, Supabase, Modal, Convex, ClickHouse and Turso, plus GitHub, Slack, Linear, Cursor, Devin, Factory, Conductor and MCP. On the observability side it works with Datadog, Honeycomb, Axiom, Grafana Cloud, Sentry, Better Stack, OpenStatus and Logfire. It also offers a REST API at api.polylane.com and an MCP server at mcp.polylane.com/mcp, and the site is machine-readable at polylane.com/llms.txt, so AI agents can use it too. Security is presented as non-negotiable: SOC 2 Type II, ISO 27001:2022, AES-256 encryption at rest, TLS 1.2+ in transit, and fully isolated data per organization. You can get started for free from the Polylane console, or install the CLI with a single command on macOS or Linux. In short, Polylane's value proposition is that your software operates itself: issues are found from the telemetry you already collect, incidents are investigated end to end, fixes arrive as reviewable pull requests, risky changes are flagged against live traffic before they merge, and the questions of on-call are answered in the tools your team already uses.