Sherlocks.ai
AI-powered SRE platform — 16+ specialized agents investigate incidents and deliver root cause to fixes in minutes, 24/7.
Overview
Sherlocks.ai is an AI-native site reliability engineering (SRE) platform that deploys 16+ purpose-built AI agents — covering domains such as Database, Kubernetes, Log Analyst, Network, CI/CD, Security, and On-call — to autonomously triage production incidents, correlate signals across the full observability stack, and deliver ranked root-cause hypotheses with remediation steps directly inside Slack. Its proprietary Awareness Graph links live telemetry with historical incident records, resolved tickets, runbook changes, and past Slack conversations so each investigation builds on institutional memory rather than starting from scratch. The platform connects to 40+ tools (AWS, GCP, Azure, Datadog, New Relic, Prometheus, PagerDuty, GitHub Actions, ELK, Kafka, and more) with read-only access, installs via a Helm-deployed Watson agent in your own VPC, and supports three deployment models: SaaS, Cloud-Native, and fully Self-Hosted with optional private LLM inference.
The company reports that teams using Sherlocks reduce alert noise by 90% and cut mean time to resolution from roughly 3.5 hours to around 22 minutes, a claimed 70% reduction in downtime. Full autonomous capability builds progressively over the first two to three months as the Awareness Graph ingests incident history, meaning teams should expect a ramp-up period before seeing peak effectiveness. Sherlocks is SOC 2 Type 2 certified and encrypts all data in transit (TLS 1.3) and at rest (AES-256), making it viable for teams with strict security and compliance requirements.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 16 Jun 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
Use cases
What you can produce with Sherlocks.ai
- Root-cause analysis report with ranked hypotheses and remediation steps delivered in Slack within minutes of alert firing
- Continuous 24/7 autonomous monitoring across cloud infrastructure, databases, Kubernetes, CI/CD, and message queues
- Awareness Graph that accumulates and correlates team incident history, runbook changes, and resolved tickets over time
- Alert correlation and deduplication reducing actionable alert volume by a claimed 90%
- Three deployment models — SaaS (in-VPC agent), Cloud-Native, Self-Hosted — with SOC 2 Type 2 and TLS 1.3/AES-256 security
- Integration connectors for a documented set of ~19 systems (AWS/GCP/Azure, Kubernetes, Datadog, New Relic, Prometheus, ELK, Kafka, GitHub Actions, Jenkins, Sentry, and major databases), with custom integrations built on request
- Flexible private LLM inference option via Azure OpenAI, AWS Bedrock, or self-hosted models for data-sensitive deployments
ASEAN Perspective
Sherlocks.ai in Southeast Asia
Sherlocks.ai was co-founded by IIT-educated engineers from India and counts several Indian tech companies (TradeIndia, Fynd, Topmate, Lokal, Stable Money, SpeakX) among its earliest customers, giving it meaningful early traction in the broader South Asia market. The integration stack — AWS, GCP, Kubernetes, Datadog, Prometheus — aligns well with what ASEAN engineering teams at growth-stage startups typically run. However, as of mid-2026 Sherlocks has no stated APAC data residency, no Singapore or SEA office, and support is US time-zone-oriented, which are practical gaps for regulated industries in Singapore, Indonesia, or the Philippines that require local data processing or SLA-backed regional support.
Sherlocks.ai stands out in the crowded AIOps/SRE space by focusing narrowly on the investigation and root-cause layer rather than trying to replace an entire incident management platform. The 16-agent architecture — with specialists for Kubernetes, databases, CI/CD, security, and on-call — means the system can reason across domain boundaries simultaneously, which is a genuine differentiation over tools that surface correlated alerts without explaining why. Early G2 reviews (4.9/5 across 28 reviews as of early 2026) are strong, and the Awareness Graph's institutional memory concept is compelling for teams that run recurring incident patterns. SOC 2 Type 2 certification and in-VPC deployment with read-only access lower the barrier for security-conscious enterprises.
The caveats are real: full autonomy requires 2–3 months of history ingestion, making it a poor fit for teams wanting instant value from day one. Slack is currently the only collaboration surface (Microsoft Teams is listed as coming soon), which excludes Teams-first organizations. With only $0.9M raised as of late 2025, the company is still in early-stage execution and the product roadmap carries execution risk. ASEAN teams will find the integration stack familiar (AWS, Datadog, Kubernetes are widely used regionally), and Indian-market customers such as TradeIndia, Fynd, and Topmate are already live, but there is no APAC-specific infrastructure, localized support, or documented regional data residency for Singapore or Southeast Asia at this time.
What people say
Sherlocks.ai holds a 4.9/5 rating across 28 G2 reviews as of early 2026 — an early but consistently positive signal. Reviewers praise the fast Slack-native root-cause delivery and the Awareness Graph's progressive institutional memory. The main criticism is a 2–3 month onboarding ramp before full autonomy. Pricing is not published publicly and is quoted via sales, with a mid-market, investigation-led positioning. As an early seed-stage startup (~$0.9M raised, roughly 9 staff), it shows strong technical depth but carries early-company execution risk. Best suited to growth-stage engineering teams (50–500 engineers) with Slack-centric workflows and recurring incident patterns.
Summary of public user & expert reviews, compiled by RECATOOLS.
Notable facts
- Gaurav Toshniwal previously scaled Doubtnut — an Indian EdTech platform — to 50 million users before co-founding Sherlocks.ai, giving him firsthand experience of the on-call pain he set out to solve.
- The platform deploys exactly 16 named specialist agents including a 'Chaos Sherlock,' a 'Compliance Sherlock,' and an 'IAM Sherlock' — covering attack surfaces most generic AIOps tools ignore.
- Sherlocks calls its architecture the 'Awareness Graph,' a living graph that correlates current telemetry with historical Slack conversations and resolved ticket threads — so the AI remembers what your team tried last time a similar alert fired.
- Despite being US-headquartered, Sherlocks.ai's earliest published reference customers are almost entirely India-based, making it one of the few SRE AI platforms with genuine South Asian design-partner roots.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including Sherlocks.ai's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Sherlocks.ai unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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