Written by: Nimesh Chakravarthi, Co-founder & CTO, Struct
Key Results You Can Expect
- Most agentic on-call platforms need 1–3 weeks for SaaS rollouts or 2–3 months for enterprise, while Struct delivers a verified 10-minute setup without migration.
- Struct connects directly to existing Datadog, PagerDuty, Slack, and GitHub stacks, so automated investigations start as soon as integrations are authenticated.
- Teams like Arcana cut average investigation time from 30 minutes to 2 minutes and reclaimed 56 developer hours per month after deploying Struct.
- Struct’s Incident Tracker performs automated resolution verification by checking live observability data, which closes the loop that manual on-call processes leave open.
- Run a 30-day risk-free Struct pilot and experience agentic on-call setup measured in minutes instead of weeks.
How Most Agentic On-Call Deployments Roll Out
Most agentic on-call deployment timelines follow a phased model that prioritizes governance over speed. Rootly AI SRE follows a 90-day phased rollout to production value with phases of read-only assistance, approval-gated actions, and narrow autonomy. Resolve.ai’s agentic platform uses conversational setup that explores the environment and stands up initial versions quickly rather than requiring a 2–3 month process. Struct’s architecture inverts that model. You authenticate three integrations, and the first automated investigation runs in under 10 minutes.
The following comparison shows how Struct’s single-step integration approach stacks up against phased rollout models and enterprise platforms.
| Platform Type | Setup Time | Phases Required | Risk Level at Launch |
|---|---|---|---|
| Struct | 10 minutes | Single-step integration (Slack, GitHub, observability) | Low, read-only investigation layer, no production actions |
| Phased SaaS (e.g., Rootly AI SRE) | 90-day phased rollout to production value | Read-only assistance, approval-gated actions, narrow autonomy | Medium, requires data hygiene, governance, and responder trust before expanding |
| Enterprise agentic platforms (e.g., Resolve.ai) | Conversational setup that stands up initial versions quickly | Environment exploration and initial testing | Low, quick conversational setup |
Run a 30-day pilot and see your first automated investigation complete today.
Real Setup Timelines for Series A–C Agentic SRE
For a 15–80 engineer SaaS team, agentic SRE setup time depends on integration complexity, not AI sophistication. Enterprise platforms demand weeks of environment indexing because they attempt to map your entire production graph before acting. Struct operates as an investigation layer on top of observability tools you already run, so there is nothing to index. A Series B fintech can authenticate Sentry, GitHub, GCP Cloud Logging, and Slack in a single session and receive automated root cause analysis on the next alert that fires.
The Arcana case study provides a concrete benchmark. Arcana’s team spent 15-plus hours per week manually triaging hundreds of high-priority Sentry alerts, with individual investigations averaging 10–45 minutes each. After integrating Struct, Arcana achieved the time savings outlined above and now runs more than 2,100 automated investigations every month. A separate internal measurement from Augment’s own deployment of an agentic investigator found the share of incidents handled autonomously by agents at Augment rose from 0.4% last quarter to 81.3% today, with related on-call metrics improving across five channels in a month. These numbers show what becomes possible when setup friction disappears.
For engineering leaders tracking MTTR and SLA compliance, the math stays straightforward. Arcana reduced senior engineer hours on investigation from approximately 60 to approximately 4 per month after adding Struct on top of Datadog. That shift redirects 56 hours of senior engineering capacity to product work every month.
Explore how Struct fits alongside your existing observability stack in the AI SRE & agentic on-call hub, or review how automated root cause analysis works end to end.
Schedule a 30-day risk-free pilot and start reclaiming engineer hours this week.
7-Step Checklist for Safe Agentic On-Call in Two Weeks
This checklist walks a Series A–C engineering team from zero to a fully operational agentic on-call setup within two weeks, without replacing existing observability tooling.
- Authenticate your alert source. Connect Slack, PagerDuty, or Linear to Struct. Designate the specific channels where production alerts fire. This trigger layer lets Struct listen and begin investigations automatically when alerts arrive.
- Connect your code repository. Link your GitHub organization. Struct uses commit history, recent deploys, and PR context to correlate code changes with alert timelines. This correlation becomes the primary mechanism for spotting regression-based root causes.
- Integrate your observability stack. Authenticate Datadog, Sentry, AWS CloudWatch, GCP Logs, or whichever combination your team runs. Struct queries these sources automatically and does not replace them. Struct integrates with leading observability platforms and is fully SOC 2 Type II and HIPAA compliant.
- Upload your on-call runbooks. Paste your team’s existing runbooks directly into Struct. The AI follows your documented procedures when an alert fires and encodes institutional knowledge that previously lived only in senior engineers’ heads.
- Run a test investigation on a known alert. Trigger a non-critical alert and review Struct’s automated output in Slack. Confirm that the root cause summary, blast radius, and suggested fixes match what a senior engineer would produce manually. Adjust runbook instructions if the output needs refinement.
- Enable incident resolution verification. Activate Struct’s Incident Tracker. It runs an approximately 1-minute automated verification loop against your observability data to confirm an incident is actually resolved before closing it. This loop closes the gap that manual on-call processes leave open.
- Expand to the full on-call rotation. After junior and mid-level engineers have reviewed two or three automated investigations, add them to the on-call rotation. Struct’s contextualized starting point for every alert makes it safe for engineers without deep systemic knowledge to take shifts confidently.
Begin your pilot and complete steps 1–3 in your first session.
How Struct Verifies Incident Resolution
Incident resolution verification is the automated process of confirming that an incident is genuinely resolved by checking observability data after a fix is applied, not by asking the engineer who applied it. True closed-loop incident management requires that the same signal that triggered detection must return to a normal state before the incident is marked resolved, and execution without verification constitutes incomplete closure. Struct’s Incident Tracker, launched August 3, 2026, implements this pattern with an approximately 1-minute automated verification loop against live observability data.
Engineering teams feel a clear operational impact from this pattern. Without automated verification, an engineer marks an incident resolved based on a subjective read of the situation, often under time pressure at 3 AM. With Struct’s verification loop, the system queries the same Datadog metrics, GCP logs, or Sentry error rates that triggered the alert and confirms the signal has normalized before closing the record. Elastic’s closed-loop architecture for automated remediation follows a Sense → Think → Act → Verify pattern, where telemetry is measured again after remediation to confirm whether the automated fix restored system health. Struct applies this same pattern as a native capability, not a custom integration project.
By combining rapid setup with automated verification, Struct holds a distinct position in the lean SaaS segment. No other platform in this space pairs agentic on-call deployment measured in minutes with closed-loop incident resolution verification in a single product. For teams bound by SLAs where every unverified closure carries audit risk, this combination matters. Learn more about how incident tracking and resolution verification work together in Struct’s incident tracking and resolution verification spoke.
SRE best practice defines resolution as the phase where the underlying problem is identified, a permanent fix is deployed, and the service is verified to be operating normally. Struct automates that verification step so your team does not have to.
Try Struct’s verification loop for 30 days and activate incident resolution checks on day one.
Frequently Asked Questions
What minimum tooling maturity is required to use Struct?
Struct works best when your team already uses at least one observability platform (Datadog, Sentry, AWS CloudWatch, GCP Logs, Grafana, or equivalent), a code repository on GitHub, and Slack or PagerDuty for alert routing. If your system lacks basic logging, trace IDs, or alerting triggers, Struct cannot deduce system state from code analysis alone. Teams already running Sentry plus cloud logs plus Slack for alerts represent the ideal starting configuration. For teams whose tooling maturity assessment includes security review requirements, compliance documentation is available at trust.struct.ai.
Can Struct operate when logs must stay inside our VPC?
Struct currently requires access to your logs and observability context via cloud integrations such as AWS, GCP, and Datadog to perform automated investigations. If your organization enforces a policy that zero logs may leave the internal network and requires full on-premises deployment, Struct is not the right fit at this time. Enterprise plan customers can discuss sidecar and on-premises support options during the demo. For the majority of Series A–C SaaS teams with compliance requirements, Struct’s cloud architecture, detailed at trust.struct.ai, satisfies security review without VPC restrictions.
What happens if our telemetry quality is inconsistent?
Struct’s investigation quality tracks closely with the quality of the telemetry it can query. Inconsistent logging, missing trace IDs, or sparse alerting coverage will produce less precise root cause summaries. The practical mitigation is to start Struct on your highest-instrumented alert channels, typically the ones where senior engineers already spend the most investigation time, and expand coverage as telemetry improves. Struct’s Deploy Guard feature, also launched August 3, 2026, adds instrumentation review at the pull request level, which improves alerting quality upstream before incidents occur.
How can junior engineers participate safely in on-call rotations with Struct?
Struct’s automated first-pass investigation produces a contextualized starting point for every alert. The output includes an impact summary, blast radius, correlated timeline across logs and traces, root cause hypothesis, and suggested fixes, all available in Slack before the engineer opens their laptop. Junior engineers no longer need deep systemic knowledge to begin triage. They review Struct’s output, validate the hypothesis, and escalate only when the situation exceeds the automated assessment. The Arcana deployment demonstrated this directly, as broader team participation in on-call triage became practical after Struct removed the requirement for tribal knowledge on every shift. Custom runbooks further encode senior engineer procedures so the AI follows your team’s exact operational steps for each alert class.
Conclusion: Put Agentic On-Call in Front of Your Next Alert
The gap between a 10-minute agentic on-call setup time and a 90-day enterprise rollout comes from architecture, not from a feature checklist. Struct operates as an investigation layer on top of the observability stack your team already runs, which means there is no environment to index, no migration to plan, and no weeks of data hygiene before the first automated investigation fires. Arcana’s results, including shorter investigations, reclaimed engineer-hours, and thousands of automated investigations per month, are achievable because the deployment barrier is measured in minutes, not quarters.
Incident resolution verification closes the loop that every manual on-call process leaves open. Struct’s Incident Tracker runs an approximately 1-minute automated check against live observability data to confirm an incident is genuinely resolved before the record closes. No other platform in the lean SaaS segment delivers both rapid deployment and closed-loop verification together.
For Series A–C engineering teams carrying SLA risk, alert fatigue, and senior-engineer bottlenecks, a 30-day risk-free pilot offers a low-friction way to validate these outcomes against your own stack. Connect your integrations in under 10 minutes, run your next on-call investigation automatically, and measure the result.
Launch your 30-day pilot, set up Struct in under 10 minutes, and let the next alert investigate itself.
