10 Best Sherlocks.ai Alternatives in 2026

Stanley Ulili
Updated on March 29, 2026

Sherlocks.ai is an AI SRE platform that autonomously investigates alerts, automates root cause analysis, and captures institutional knowledge from past incidents. It analyzes alerts in 2-3 minutes by correlating APM metrics, traces, logs, code repositories, build systems, and Slack conversations.

But Sherlocks.ai has specific limitations. It does not generate pull requests or code fixes (on the roadmap but not yet available). It has no built-in incident management, on-call paging, or status pages. Its customer base skews toward Indian startups and growth-stage companies, with limited publicly documented enterprise adoption. And pricing reportedly starts around $1,500/month, which is significant for smaller teams.

This guide compares the 10 best Sherlocks.ai alternatives for teams that need code-level remediation, built-in incident management, broader enterprise validation, or more flexible pricing.

Why do teams look for Sherlocks.ai alternatives?

Sherlocks.ai's Slack-native investigation and institutional knowledge capture are genuinely useful. But teams evaluate alternatives for practical reasons:

No code fix generation yet. Sherlocks.ai provides high-level remediation suggestions but does not generate pull requests, draft code fixes, or execute infrastructure commands. Teams that want the AI to close the loop from diagnosis to fix need tools that go further. Code-fix generation is on the roadmap but not shipped.

No built-in incident management. Sherlocks.ai tags owners in Slack but does not provide on-call scheduling, phone/SMS paging, escalation routing, incident timelines, status pages, or post-mortem workflows. Teams need PagerDuty or a similar tool alongside it.

Limited enterprise customer evidence. Sherlocks.ai's named customers (Topmate, TradeIndia, Robylon, Repos Energy, Suprsend, InterviewVector) are primarily Indian startups and mid-size companies. Teams at larger enterprises or regulated industries may want broader validation before committing.

Pricing starts at ~$1,500/month. For a tool that provides investigation and suggestions but not fixes, incident management, or observability, this is a significant commitment. Teams with tighter budgets may find better value in platforms that include more for less.

No built-in observability. Sherlocks.ai connects to your existing APM and monitoring tools but does not provide its own log management, metrics collection, tracing, or uptime monitoring. You still need a full stack underneath it.

Slack-only delivery. Results are delivered primarily through Slack. There is no dedicated web dashboard for reviewing investigation history, browsing past RCAs, or managing system health outside of Slack threads.

How do Sherlocks.ai alternatives compare?

Tool Best for Root cause approach Generates code fixes Incident management Pricing
Better Stack Full observability + AI SRE + incident management in one eBPF service map + OTel traces + logs + metrics Yes (PRs in GitHub) Built-in on-call, status pages, timelines Free tier, $29/responder/month
Resolve AI Most autonomous enterprise-scale investigation Multi-agent parallel hypothesis testing Yes (PRs, kubectl, scripts) No Enterprise (custom)
incident.io AI SRE with deep incident coordination Telemetry + code changes + incident history Yes (PRs from Slack) Built-in on-call, status pages, workflows ~$31-45/user/month
Rootly Transparent chain-of-thought with incident platform Code changes + telemetry + past incidents No (suggestions only) Built-in on-call, retrospectives, status pages From $20/user/month
Datadog Bits AI Deepest native data for Datadog teams Native Datadog telemetry Yes (code fixes) Separate Datadog product $500/20 investigations/month
IncidentFox Zero-setup with executable fix scripts Codebase + Slack history + past incidents Yes (fix scripts) No Free tier, enterprise on request
Cleric Self-learning hypothesis-driven diagnosis Hypothesis trees + logs + metrics + infra state No (read-only) No Free start, custom plans
Deeptrace Compounding accuracy via knowledge graph Living knowledge graph + telemetry + code Yes (PRs, runbooks, Linear) No Startup and Enterprise tiers
Dash0 Agent0 OTel-native multi-agent observability Multi-agent guild (6 agents) No (dashboards and alerts) No From ~$50/month
LogicMonitor Edwin AI Enterprise hybrid IT with self-healing Event intelligence + historical patterns Yes (playbook execution) Integrated with ServiceNow Enterprise pricing

1. Better Stack

Screenshot of Better Stack AI SRE

Better Stack addresses every limitation in Sherlocks.ai's architecture at once. Sherlocks.ai investigates alerts using data from your existing tools and delivers suggestions in Slack. Better Stack collects the telemetry itself, investigates with AI, generates code fixes, and manages the full incident lifecycle without requiring a single external tool.

What makes Better Stack the strongest Sherlocks.ai alternative?

Sherlocks.ai needs your Datadog, your Grafana, your PagerDuty, and your Slack to function. Better Stack replaces all of them. Logs, metrics, OpenTelemetry traces, error tracking, real user monitoring, uptime checks, on-call rotation, escalation, status pages, and an AI SRE agent all live in one product. The AI investigates using data it collected natively through eBPF, so there are no integration gaps between where your telemetry lives and where the investigation happens.

Sherlocks.ai suggests remediation. Better Stack acts on it. When the AI identifies a code-related root cause, it opens a pull request in GitHub. It drafts post-mortems from the incident timeline, creates Linear tickets for follow-up, and answers your questions with embedded charts. Sherlocks.ai lists code-fix generation as "on the roadmap." Better Stack ships it today.

Sherlocks.ai has no on-call, no paging, no status pages. Better Stack includes all three. When an alert fires, the AI investigates while the on-call engineer is paged. The status page updates automatically. The post-mortem writes itself. No PagerDuty subscription needed.

Pricing is $29/responder/month with a free tier and a 60-day money-back guarantee. Sherlocks.ai starts at approximately $1,500/month for investigation-only capabilities. Better Stack gives you the full platform for less.

The agent runs across Slack, Microsoft Teams, and Claude Code via MCP server. Every action requires your approval first.

🌟 Key features

  • Native telemetry via eBPF auto-instrumentation and OpenTelemetry, no external monitoring required
  • Service map visualization tracking error propagation across services during incidents
  • Every AI query visible and verifiable for full investigation transparency
  • Root cause documents with evidence chains, log citations, and resolution steps
  • Pull request generation in GitHub when errors are detected
  • Natural language questions answered with inline charts
  • Linear tickets, AI post-mortems, and automated trace/log analysis
  • MCP server for Claude Desktop and Claude Code
  • On-call scheduling, escalation routing, incident timelines, and hosted status pages
  • eBPF infrastructure visibility with zero code changes

βž• Pros

  • Replaces the observability tools Sherlocks.ai depends on plus the incident management it lacks
  • Generates PRs and code fixes that Sherlocks.ai has on the roadmap but does not yet ship
  • On-call, paging, status pages, and post-mortems included rather than requiring PagerDuty
  • $29/responder/month versus Sherlocks.ai's ~$1,500/month starting price
  • Available on Slack, Microsoft Teams, and web (not Slack-only)
  • Free tier to start with no sales conversation required
  • 60-day money-back guarantee
  • SOC 2 Type 2, GDPR, ISO 27001 certified

βž– Cons

  • Investigation depth relies on natively ingested data rather than third-party tools alone

πŸ’² Pricing

$29/responder/month for the full platform. Free tier covers 10 monitors, 3 GB logs (3-day retention), and 2B metrics (30-day retention). Enterprise pricing available. 60-day money-back guarantee. No demo required to start.

2. Resolve AI

Screenshot of Resolve AI

Resolve AI is a multi-agent AI SRE founded by OpenTelemetry co-creators Spiros Xanthos and Mayank Agarwal. It raised $125M at a $1B valuation in February 2026. Customers include Coinbase, DoorDash, MongoDB, Salesforce, and Zscaler.

How does Resolve AI compare to Sherlocks.ai?

Both investigate incidents autonomously. The differences are scale, remediation, and customer validation. Resolve AI generates PRs, kubectl commands, code fixes, and scripts. Sherlocks.ai provides suggestions only. Resolve AI has enterprise customers (Coinbase, DoorDash, Salesforce) with publicly documented results: 72% faster investigations at Coinbase, 87% faster at DoorDash. Sherlocks.ai's customer base is primarily Indian growth-stage companies.

Resolve AI's multi-agent system pursues multiple hypotheses in parallel across code, infrastructure, and telemetry simultaneously.

🌟 Key features

  • Multi-agent parallel hypothesis testing across code, infrastructure, and telemetry
  • 100% of alerts investigated in under 5 minutes
  • Generates PRs, kubectl commands, code fixes, and scripts
  • Learns from historical patterns and runbooks
  • SOC 2 Type II, GDPR, HIPAA

βž• Pros

  • Code-level remediation that Sherlocks.ai does not yet offer
  • Broader enterprise customer validation (Coinbase, DoorDash, Salesforce)
  • $1B valuation signals long-term viability
  • Full compliance certifications

βž– Cons

  • Pricing not public, reportedly $1M+/year for large deployments
  • No built-in observability or incident management
  • No institutional knowledge capture in the way Sherlocks.ai emphasizes

πŸ’² Pricing

Free trial. Custom enterprise pricing.

3. incident.io AI SRE

Screenshot of incident.io AI SRE

incident.io AI SRE is an AI investigation agent inside a mature incident management platform with on-call, status pages, and escalation.

What does incident.io provide that Sherlocks.ai does not?

Sherlocks.ai investigates alerts but has no incident management. incident.io provides the full incident lifecycle: on-call paging, escalation routing, status pages, post-mortem generation, and AI-powered investigation all in one platform. It also generates code fixes and opens PRs from Slack, which Sherlocks.ai cannot do yet.

incident.io leverages years of historical incident data for pattern-matching, identifies the exact PR behind failures, and operates with a web UI alongside Slack.

🌟 Key features

  • Telemetry, code changes, and historical incident correlation
  • PR identification and code fix drafting from Slack
  • AI-native post-mortems
  • Full on-call, status pages, and escalation

βž• Pros

  • Incident lifecycle management Sherlocks.ai lacks (on-call, paging, status pages)
  • Generates code fixes and PRs that Sherlocks.ai does not
  • Web UI alongside Slack
  • 5x faster resolution reported
  • More transparent pricing (~$31-45/user/month)

βž– Cons

  • Depends on external observability tools
  • AI SRE pricing requires sales
  • No auto-discovery or institutional knowledge capture like Sherlocks.ai

πŸ’² Pricing

Platform ~$31-45/user/month. AI SRE pricing requires demo.

4. Rootly AI SRE

Screenshot of Rootly AI SRE

Rootly AI SRE is an AI investigation layer on an incident platform used by NVIDIA, LinkedIn, Figma, Canva, and Replit since 2021.

Why would a team choose Rootly over Sherlocks.ai?

Rootly provides incident management, on-call, retrospectives, and status pages that Sherlocks.ai lacks. It shows full chain-of-thought reasoning at every investigation step, offering more transparent AI logic than Sherlocks.ai's summary-style findings. Rootly's customer base (NVIDIA, LinkedIn, Figma, Canva) represents broader and more publicly documented enterprise adoption.

Rootly starts at $20/user/month with a 14-day free trial, which is significantly less than Sherlocks.ai's reported $1,500/month entry point.

🌟 Key features

  • Chain-of-thought transparency for every investigation
  • MCP server for IDE integration (Cursor, Windsurf, Claude)
  • Full on-call, retrospectives, and status pages
  • Bring-your-own AI API key, PII scrubbing

βž• Pros

  • Incident lifecycle management Sherlocks.ai lacks
  • More transparent investigation reasoning
  • Broader enterprise customers (NVIDIA, LinkedIn, Figma)
  • $20/user/month versus ~$1,500/month
  • 14-day free trial

βž– Cons

  • Does not generate PRs or execute fixes
  • Depends on external observability
  • No auto-discovery or Slack conversation mining like Sherlocks.ai
  • No institutional knowledge learning system

πŸ’² Pricing

14-day free trial. Starts at $20/user/month.

5. Datadog Bits AI SRE

Screenshot of Datadog Bits AI SRE

Datadog Bits AI SRE is an autonomous AI SRE with native access to Datadog's full observability dataset. GA since December 2025, validated across 2,000+ environments.

How does Bits AI compare to Sherlocks.ai?

Sherlocks.ai reads from Datadog through integrations. Bits AI SRE lives inside Datadog with native, unfiltered access to every metric, log, trace, RUM session, and profiler signal. For Datadog customers, this means deeper investigation data than Sherlocks.ai can achieve from outside the platform. Bits AI also suggests code fixes via the Dev Agent, which Sherlocks.ai has not yet shipped.

iFood reports 70% MTTR reduction from day one.

🌟 Key features

  • Native Datadog data access without integration limits
  • Parallel root cause exploration
  • Code fix suggestions via Bits AI Dev Agent
  • Feedback loops improving accuracy
  • RBAC, HIPAA compliance

βž• Pros

  • Deeper data access for Datadog customers than Sherlocks.ai's integration model
  • Code fix generation Sherlocks.ai does not yet offer
  • 2,000+ environments validated
  • Published pricing

βž– Cons

  • Per-investigation pricing ($500/20 per month) can escalate
  • Only valuable in Datadog ecosystem
  • No institutional knowledge capture
  • No auto-discovery from Slack conversations

πŸ’² Pricing

$500 per 20 investigations/month (annual). 14-day free trial.

6. IncidentFox

Screenshot of IncidentFox

IncidentFox is a YC W26-backed AI investigator with 300+ built-in tools and zero-setup onboarding.

What does IncidentFox offer that Sherlocks.ai does not?

IncidentFox delivers executable fix scripts with one-click approval, directly addressing Sherlocks.ai's remediation gap. It auto-learns your stack from codebase analysis and Slack history similar to Sherlocks.ai, but ships with 300+ built-in tools versus Sherlocks.ai's integration catalog. The open core Apache 2.0 license provides self-hosting flexibility.

IncidentFox is free to start. Sherlocks.ai reportedly starts at $1,500/month.

🌟 Key features

  • 300+ built-in tools with auto-generated integrations
  • Executable fix scripts with one-click approval
  • Zero-setup auto-learning from codebase and Slack
  • Open core (Apache 2.0) self-host option

βž• Pros

  • Executable fix scripts beyond Sherlocks.ai's suggestions-only model
  • Free to start versus ~$1,500/month
  • 300+ tools for broader connectivity
  • Open core for self-hosting

βž– Cons

  • Very early-stage (YC W26, two-person team)
  • SOC 2 Type 2 in progress
  • Slack-only
  • No institutional knowledge system as mature as Sherlocks.ai's

πŸ’² Pricing

Free to start. Enterprise pricing requires demo.

7. Cleric

Screenshot of Cleric

Cleric is a self-learning AI SRE with hypothesis-driven reasoning. Gartner Cool Vendor 2025 in AI for SRE and Observability. 200,000+ production investigations, 92% actionable findings, $9.8M raised from Vertex Ventures US and Zetta Venture Partners.

How does Cleric compare to Sherlocks.ai?

Both emphasize learning from past incidents. Sherlocks.ai captures institutional knowledge from resolutions and Slack conversations. Cleric uses a more structured self-learning architecture with semantic, episodic, and procedural memory that evolves without manual tuning. Cleric shows hypothesis trees for investigation transparency, while Sherlocks.ai delivers summary-style findings.

Cleric has completed 200,000+ investigations with 92% actionable findings. However, like Sherlocks.ai, Cleric is read-only and does not generate code fixes.

🌟 Key features

  • Hypothesis-driven investigation with transparent reasoning trees
  • Self-learning across semantic, episodic, and procedural memory
  • Live architecture mapping
  • Confidence scores for every finding
  • SOC 2 Type II compliant

βž• Pros

  • More sophisticated learning architecture than Sherlocks.ai's knowledge capture
  • Hypothesis tree transparency exceeds summary-style findings
  • Gartner Cool Vendor recognition
  • 92% actionable findings across 200,000+ investigations
  • Free to start

βž– Cons

  • Read-only, no code fix generation (same limitation as Sherlocks.ai)
  • No incident management or on-call
  • Pricing not public for larger plans
  • Smaller company ($9.8M vs Sherlocks.ai's undisclosed funding)

πŸ’² Pricing

Free to start. Custom plans available.

8. Deeptrace

Screenshot of Deeptrace

Deeptrace builds a living knowledge graph of your system architecture that delivers compounding root cause accuracy over time.

What does Deeptrace offer beyond Sherlocks.ai?

Both learn from your systems over time. Sherlocks.ai captures knowledge from Slack conversations, prior RCAs, and technical docs. Deeptrace builds a persistent architectural model mapping service dependencies and failure patterns continuously. Deeptrace also generates PRs, updates runbooks, and creates Linear tickets, going beyond Sherlocks.ai's suggestion-only output.

Evidence-backed root causes arrive with citations in 2-3 minutes. Endorsed by Gary Tan, president of Y Combinator.

🌟 Key features

  • Living knowledge graph updated in real-time
  • Root cause with citations in 2-3 minutes
  • PR generation, runbook updates, Linear tickets
  • 20+ integrations

βž• Pros

  • Generates PRs and remediation artifacts Sherlocks.ai cannot
  • Knowledge graph offers structural learning beyond conversation mining
  • 70%+ root cause accuracy
  • Under 1 hour setup

βž– Cons

  • 1,000 alerts/month cap on Startup plan
  • Early-stage ($5M seed)
  • No incident management
  • No Slack conversation mining or auto-discovery like Sherlocks.ai

πŸ’² Pricing

Startup: 2-week trial, 1,000 alerts/month. Enterprise: custom capacity.

9. Dash0 Agent0

Screenshot of Dash0 Agent0

Dash0 Agent0 is six specialized agents inside an OpenTelemetry-native observability platform. Dash0 acquired Lumigo for serverless coverage.

When does Dash0 make sense over Sherlocks.ai?

Dash0 provides built-in observability that Sherlocks.ai depends on external tools for. Six agents cover investigation, PromQL queries, OTel onboarding, trace analysis, dashboard creation, and frontend performance. This breadth addresses observability tasks Sherlocks.ai does not touch. Transparent pricing starts at $50/month versus ~$1,500/month.

🌟 Key features

  • Six specialized agents, OTel-native platform
  • Built-in observability
  • Transparent pricing from $50/month

βž• Pros

  • Built-in observability Sherlocks.ai lacks
  • Transparent pricing significantly below Sherlocks.ai's entry point
  • OTel-native portability
  • Broader agent capabilities beyond investigation

βž– Cons

  • Still in Beta
  • No fix generation or incident management
  • No institutional knowledge learning
  • Newer ecosystem

πŸ’² Pricing

Free trial. Starts at approximately $50/month.

10. LogicMonitor Edwin AI

Screenshot of LogicMonitor Edwin AI

LogicMonitor Edwin AI is an enterprise AIOps platform with 3,000+ integrations and bi-directional ServiceNow sync.

When does Edwin AI make sense over Sherlocks.ai?

Edwin AI serves enterprise IT operations managing hybrid environments with legacy systems and multi-cloud at a scale beyond Sherlocks.ai's growth-stage focus. Its 3,000+ integrations, autonomous playbook execution, and ServiceNow sync cover enterprise ITSM workflows that Sherlocks.ai was not designed for. Customer results include 67% ITSM incident reduction and 88% noise reduction at companies like Syngenta and Capital Group.

🌟 Key features

  • 3,000+ integrations, bi-directional ServiceNow sync
  • Autonomous playbook execution
  • Predictive outage prevention
  • 67% incident reduction, 88% noise reduction

βž• Pros

  • Enterprise-grade with 3,000+ integrations
  • Self-healing through playbook execution
  • Proven at major enterprises (Syngenta, Capital Group, Topgolf)

βž– Cons

  • Overkill for growth-stage teams
  • Enterprise pricing through sales
  • Traditional ITOps focus
  • Significant learning curve

πŸ’² Pricing

Enterprise pricing. Requires demo.

Final thoughts

Sherlocks.ai brings valuable institutional knowledge capture and Slack-native investigation for fast-growing teams. But its missing code-fix generation, absent incident management, limited enterprise validation, and ~$1,500/month starting price leave gaps that more complete platforms fill.

If you want a single product that collects telemetry, investigates with AI, generates code fixes, and manages the full incident lifecycle, Better Stack covers the entire workflow for $29/responder/month. It replaces the monitoring stack Sherlocks.ai reads from, adds the PR generation Sherlocks.ai has not yet shipped, and includes on-call and status pages Sherlocks.ai leaves to PagerDuty. Free tier, 5-minute setup, no sales call required.