⚡Stack Radar

Prompt Management · Reviewed 19 Oct 2026

Latitude

Open-source AI agent monitoring platform for production teams.

from $99 · free tier · latitude.so ↗

Paid against free › Prompt Management › Latitude

Latitude at a glance

SEO analysis

Collected Oct 19, 2026

latitude.so: an estimated 69,500 total monthly visits and about 617 monthly organic visits across 611 ranking keywords. Scout crawled 15 pages and measured a technical health score of 96/100.

69.5KEstimated total trafficModeled monthly visits611Ranking keywordsPublic search sample96/100Technical health15 pages checked2KReferring domainsLive backlink summary

Overview

01

Summary

The useful answer before the supporting detail.

Latitude is an open-source AI agent monitoring platform that helps teams detect, prioritize, and resolve production agent failures S1. It is used by teams building agents at scale to gain visibility into agent behavior and act on issues before users complain S1. The platform provides automatic issue grouping, golden datasets, and integrations with Slack, email, and webhooks, enabling teams to improve agent reliability S1.

02

Product identity and positioning

Name, category, positioning, audience, and first-party claims.

  • Identity: Latitude is an open-source AI agent observability and monitoring platform S1.
  • Core purpose: It solves the problem of detecting and resolving production agent failures S1.
  • Intended users: Teams building AI agents at scale S1.
  • Product scope: Latitude is a monitoring platform, not a broader product family; it includes features like issue grouping, golden datasets, and alerts S1.
  • Positioning: The vendor positions Latitude as "agent monitoring without the hassle" S1.
  • Claimed distinction: Latitude claims to automatically group recurring failures and prioritize them, with trend and failing traces attached S1.
03

Use cases and audiences

Who the product serves and the jobs it is designed to handle.

AudiencePractical use case
Teams building AI agents at scaleMonitor production agent behavior to detect and resolve failures S1.
Engineering teamsSet up Latitude in their project and discover what their agent is really doing in less than 5 minutes S1.
Teams needing complianceKeep data in Europe with hosted data stored and processed on European servers S1.

Features

09

Features and capabilities

Core functions and evidence-backed product capabilities.

CapabilityWhat it does
Automatic issue groupingRecurring failures are grouped and prioritized automatically, with trend and failing traces attached S1.
Golden datasetsGolden datasets are built automatically from validated production traces S1.
AlertingGet notified when a new issue is detected or an existing one escalates S1.
Session intelligenceAnalyzes completed sessions to extract what the conversation was about, what happened, and where things got spicy S1.
Signal definitionDefine a signal for any behavior you want to track — a failure mode, policy, or quality check — and Latitude detects it on every matching session S1.
Inline feedbackLeave inline feedback on any trace, span, or output S1.
Dataset managementManage datasets for evaluation and testing S1.
Search and filtersSemantic search, exact text, and metadata filters combined S1.
10

Integrations and ecosystem

Connected products, exports, APIs, and workflow compatibility.

Integration or interfaceTypeWhat it enables
SlackIntegrationConnect to Slack so your team can act before users complain S1.
EmailIntegrationConnect to email for notifications S1.
WebhooksIntegrationConnect to webhooks for notifications S1.
MCP serverAI interfaceConnect the Latitude MCP to run the whole loop without leaving your editor S1.
OpenTelemetryIntegrationPoint your existing Open Telemetry pipeline at Latitude and traces show up S1.
SDKSDKDrop in our SDK and traces show up S1.

Pricing

11

Pricing and plans

Published plans, free access, trials, credits, and pricing limitations.

Plan or offerVerified price and billingIncludedLimits
Free$0 per month S28Traces and signals included; unlimited seats S2830-day retention S28
Pro$99 per month S28Credits; unlimited seats S2890-day retention; extra credits $20 per 10K S28
CustomContact sales S28Custom credit volume; unlimited seats S28SAML SSO, custom retention S28

Competition

12

Competitive landscape

Domains competing for the same organic search demand.

Sampled competitors

CompetitorFirst-page appearancesSampled queriesAverage positionQueries observed
arize.com513.8arize pricing
studypug.com111domain vocabulary
ilclassroom.com112domain vocabulary
colorincolorado.org113domain vocabulary
youtube.com114domain vocabulary
quizlet.com115domain vocabulary
vendr.com115arize pricing
researchgate.net116domain vocabulary
cekura.ai116arize pricing
brainly.com117domain vocabulary

Website intelligence — Collected evidence

Customers, testimonials, and first-party review claims

No supporting public-page evidence was collected for this category.

Independent review sources discovered

No links to supported independent review platforms were discovered on the collected pages.

14

AI visibility

Measured ChatGPT and Google AI mentions with cited sources.

AI-assistant referral traffic

  • Estimated current generative-AI referral share: 1.6%

Scout traffic model did not return a separate AI-referral trend series for this domain.

Website intelligence — Collected evidence

Site-stated AI capabilities

Page typeEvidenceSource
otherOpen-source AI agent monitoring platform. Full observability into whathttps://latitude.so/
featuresLatitude is an open-source, MIT-licensed platform for monitoring and improving production AI agents.https://latitude.so/product.md
featuresLatitude is designed for teams that operate AI agents or AI-enabled product features in production.https://latitude.so/product.md
featuresSoftware engineers responsible for AI featureshttps://latitude.so/product.md
featuresTeams scaling an AI feature beyond an initial implementationhttps://latitude.so/product.md
featuresGarak systematically red-teams LLM security vulnerabilities — a distinct, complementary evaluation dimension that traditional benchmarks also miss.https://latitude.so/blog/agent-evaluation-tools-comparison-product-specific-vs-generic-benchmarks
featuresEvery AI team reaches the same moment eventually. Your agent scores well on every benchmark you’ve built. Your LLM-as-judge says outputs are high quality. Your eval suite is green. Then you deploy, and production tells a different story — failures that weren’t in any dataset, edge cases you didn’t anticipate, failure patterns that only emerge across conversation turns or through sequences of tool calls.https://latitude.so/blog/agent-evaluation-tools-comparison-product-specific-vs-generic-benchmarks
featuresThe problem isn’t that you evaluated badly. It’s that you evaluated the wrong thing. Generic benchmarks and LLM evaluation tools were built for a fundamentally different system than the one you’re running.https://latitude.so/blog/agent-evaluation-tools-comparison-product-specific-vs-generic-benchmarks
featuresMost AI evaluation tooling was designed during the LLM completion era: one prompt, one response, one score. The evaluation surface was bounded and stable. You could write a golden dataset, score against it, and get a meaningful signal about quality. For simple LLM workflows, this still works. For production agents — systems that plan across multiple steps, invoke external tools, manage state across conversation turns, and follow non-deterministic execution paths — it doesn’t.https://latitude.so/blog/agent-evaluation-tools-comparison-product-specific-vs-generic-benchmarks
featuresThis guide compares eight evaluation tools across criteria that specifically matter for agents. It includes purpose-built agent platforms, established LLM eval frameworks, and academic toolkits. The goal is to help you match your evaluation approach to the actual complexity of the system you’re building.https://latitude.so/blog/agent-evaluation-tools-comparison-product-specific-vs-generic-benchmarks
featuresFor LLM evaluation, the unit of analysis is the individual request/response pair. Score it, aggregate scores, track trends. This is tractable because the failure mode — a poor completion given an input — is visible within the unit.https://latitude.so/blog/agent-evaluation-tools-comparison-product-specific-vs-generic-benchmarks
featuresBlog›Complete guide to AI product architecture for GenAIhttps://latitude.so/blog/ai-product-architecture-guide-genai
featuresComplete guide to AI product architecture for GenAIhttps://latitude.so/blog/ai-product-architecture-guide-genai
featuresDiscover the 6 essential layers of AI product architecture for building effective generative AI systems. Learn best practices, tools, and strategies for success.https://latitude.so/blog/ai-product-architecture-guide-genai
featuresArtificial Intelligence (AI) and large language models (LLMs) are revolutionizing product development across industries. From enhancing user experiences to automating intricate processes, generative AI (GenAI) systems are positioning themselves as critical tools for solving complex business challenges. However, their success hinges on one crucial factor: a well-structured AI product architecture.https://latitude.so/blog/ai-product-architecture-guide-genai
featuresThis article outlines the key principles, strategies, and components required to build effective AI product architectures for GenAI systems. Whether you’re a product manager striving to improve AI quality or a technical practitioner implementing LLM features, this guide offers actionable insights to help you create systems that are scalable, adaptable, and user-centric.https://latitude.so/blog/ai-product-architecture-guide-genai
featuresAI product architecture is more than just deploying a large language model and calling it a solution; it is a multi-layered blueprint that facilitates the design, development, and delivery of intelligent systems. To understand its significance, consider a traditional product architecture where deterministic workflows and fixed logic dominate. GenAI systems, by contrast, are probabilistic, context-aware, and adaptive, requiring a paradigm shift in how products are designed.https://latitude.so/blog/ai-product-architecture-guide-genai
featuresObservability and Governance : Monitoring AI behavior and ensuring it aligns with responsible AI principles is essential for long-term sustainability.https://latitude.so/blog/ai-product-architecture-guide-genai
featuresThis is where users interact with the system, making it the starting point for all AI applications. A thoughtfully designed UX layer ensures intuitive navigation, supports diverse input formats (e.g., text, images, or audio), and fosters trust through transparency.https://latitude.so/blog/ai-product-architecture-guide-genai
featuresWhen transferring a large language model (LLM) to a new domain, the model often encounters data that it wasn’t originally built to handle. This mismatch leads to gradient interference , where the model’s existing knowledge clashes with the new information it needs to learn. Studies reveal that 67% of parameters in attention query and key projection matrices can experience this conflict during the adaptation process. Essentially, the model struggles to balance what it already knows with the demands of the new domain.https://latitude.so/blog/cross-domain-model-transfer-challenges-solutions

These are first-party product claims, not independent measurements of AI-search visibility.

15

Marketing opportunities

Actions calculated directly from the collected evidence.

OpportunityRecommended actionEvidence
Competitor gapReview the sampled queries where arize.com appears.5 first-page appearances across arize pricing

Website intelligence — Collected evidence

Website evidence gaps

  • integrations: no usable public page was collected; verify whether the site publishes this evidence.
  • customers: no usable public page was collected; verify whether the site publishes this evidence.
  • reviews: no usable public page was collected; verify whether the site publishes this evidence.
  • changes: no usable public page was collected; verify whether the site publishes this evidence.
  • identity: no usable public page was collected; verify whether the site publishes this evidence.
  • technical: no usable public page was collected; verify whether the site publishes this evidence.

Trust and proof

16

Customers, proof, and reviews

Published proof, customer signals, and review evidence.

Independent reviews

PlatformPageHow it was foundNote
docs.latitude.soHow to use Latitude - Latitude DocsGrounded web searchtraces from your agent to Latitude. Each interaction becomes a trace of spans (LLM calls, tool calls, retrieval, and ... group into sessions. Send a `userId` and ... ` so you can also break activity down per user and review reliability, errors
docs.latitude.soSelf-Healing Agents - Latitude DocsGrounded web searchA self-healing agent is one whose production failures reach a coding agent automatically, with the evidence attached ... and the fix lands as a pull request that a person reviews, backed by a regression test in your CI.

Customer proof

No named customers, testimonials, or customer case studies were found.

Independent mentions

  • Make your AI agents self-healing — ## Make your AI agents self-healing Latitude traces your agent in production, finds the failures, and dispatches your coding agent to fix them. ... your existing Open Telemetry pipeline at Latitude and traces show up. No proprietary format, no
  • Overview - Latitude Docs — Latitude observability shows what your agent did in production. It captures the execution path for each interaction, including LLM calls, tool calls, retrieval steps, metadata, timing, token usage, cost, and errors. For the complete product vocabulary, see Core Concepts. This page focuses on the telemetry data you inspect in the Observability area. ... Latitude uses three telemetry levels: - Spans: individual operations such as LLM calls, tool invocations, retrieval steps, HTTP requests, or cust
  • LLM Observability for AI Agents / Latitude — Capture real inputs, outputs, and context from live traffic to understand what your system is actually doing ... Capture real inputs, outputs, and context from live traffic. Understand what your system is actually doing, not what you expect it to do.
  • Latitude Overview - Latitude Docs — Latitude is an open-source, MIT-licensed platform for improving production AI agents. It helps teams capture real agent traffic, understand what is going wrong, and turn repeated failures into tracked signals you can monitor and fix. The product is organized around the loop you work in every day: Observe, Understand, Refine. ... Latitude starts by collecting agent telemetry. Each interaction becomes a trace made of spans for LLM calls, tool calls, retrieval steps, and other instrumented work. Re
  • Traces - Latitude Docs — - Root span name: The top-level operation name - Overall status: OK or error, derived from constituent spans - Total duration: End-to-end timing - Aggregated tokens: Total input and output tokens across
  • Developer Quick Start - Latitude Docs — sidebar for provider- and framework-specific instructions. Once telemetry is connected, every LLM call, tool invocation, and agent step your application makes will appear as spans ... grouped into traces (single interactions) and sessions
  • Latitude product reference — It captures production agent telemetry, helps teams discover recurring failures, turns those failures into tracked signals, dispatches a customer-controlled coding agent with the relevant evidence, and verifies fixes using production-derived tests and
  • Core Concepts - Latitude Docs — watches a target, such as a signal, a saved search, a tool, or your raw traffic, and opens an incident when a condition is met. When an incident ... . Every project comes with system monitors that watch the signal lifecycle, and you can create your own.

External links were grounded in one live web search. Search snippets are leads, not independently scraped page content; rejected links remain available in Review evidence.

17

Company, security, and trust

Ownership, policies, security signals, and public trust evidence.

SignalFindingSource
Company and ownershipLatitude also enables live evaluations of production logs, tracking metrics like safety, helpfulness, and hallucination rates in real-time. Using smaller, specialized language models (SLMs) for quality checks can cut evasource
Contact and supportNot published on the collected pages.—
Legal and privacyCan I upgrade, downgrade, or cancel my plan anytime?source
Security and complianceYour data is protected with industry-leading standards. We are SOC 2 certified and built to meet the requirements of the most security-conscious teams.source
Uptime and status pageUptime and support SLAsource

Not found on the collected pages: contact and support. This only means Scout did not find it on the pages it read; it says nothing about the company itself.

18

Documentation and product updates

Help resources, product guidance, and visible changes over time.

Resource or updateTypeWhat is availableDate or freshness
Complete guide to AI product architecture for GenAI / LatitudeGuideGuides, comparisons, pricing breakdowns, use cases, and how-to articles. (source)Not dated
How to build scalable LLM features: A step-by-step guide / LatitudeGuideLearn how to effectively build scalable LLM features using distributed systems, microservices, and optimization techniques for improved performance. (source)Not dated
How to validate prompts for task-specific AI features / LatitudeGuideGuides, comparisons, pricing breakdowns, use cases, and how-to articles. (source)Not dated
Agent evaluation tools compared: Why generic benchmarks fail production AI (2026) / LatitudeProduct updateProduct update is publicly available. (source)Not dated
Agent evaluation tools compared: Why generic benchmarks fail production AI (2026) / LatitudeSupportPublic contact and support channel. (source)Not dated
Complete guide to AI product architecture for GenAI / LatitudeRoadmapPublic product roadmap. (source)Not dated

Not found in the collected public sources: changelog or release notes, status page, separate help center or knowledge base.

Technical

19

Technical and delivery signals

Delivery model, platforms, API, data ownership, reliability claims and release activity.

SignalFindingSource
Delivery model (cloud, self-hosted, desktop, browser extension)Cloud for high volume products or deploy in your infrastructure S28.S28
Platforms and appsNot published on the collected pages.—
API and extensibility (API, SDK, webhooks, MCP, plugins)Connect to Slack, email, or webhooks S1; MCP server available S1; SDK available S1.S1
Data ownership and exportDetailed, exportable activity and access logs S1.S1
Performance and reliability claimsNot published on the collected pages.—
Release activityNot published on the collected pages.—
20

Measured infrastructure

Domain, certificate, and hosting signals, measured directly.

SignalFinding
First archived2022-02-14 — web archive
TLS certificateLet's Encrypt, valid, expires 2026-12-04
Security headersHSTS
Headers not servedCSP, X-Content-Type-Options, X-Frame-Options, Referrer-Policy
Server headerVercel
Mail handled byaspmx.l.google.com, alt2.aspmx.l.google.com
Nameserversns-55.awsdns-06.com, ns-944.awsdns-54.net

Not measurable: rdap: no RDAP server published for .so. A gap here means the lookup was unavailable, not that the finding is negative.

21

Technical site audit

A bounded multi-page crawl with page-level issues and URLs.

Scout — Bounded technical crawl

  • Pages crawled: 15 of 15 maximum
  • Technical health: 96/100
  • Critical issues: 0
  • Warnings: 8
  • Notices: 9

Issues

SeverityIssueValueAffected URL
noticeImages are missing alt text4https://latitude.so/
noticeImages are missing alt text2https://latitude.so/pricing
noticeLow visible word count145https://latitude.so/customers
noticeMeta description length should be reviewed11https://latitude.so/changelog
noticeMeta description length should be reviewed39https://latitude.so/terms
noticeMeta description length should be reviewed41https://latitude.so/privacy
warningTitle length should be reviewed92https://latitude.so/customers/heytavi
noticeMeta description length should be reviewed194https://latitude.so/customers/heytavi
noticeMeta description length should be reviewed237https://latitude.so/compare
warningTitle length should be reviewed67https://latitude.so/developers
noticeMeta description length should be reviewed234https://latitude.so/developers
warningPage should have one primary H10https://latitude.so/changelog/agent-score
warningPage should have one primary H10https://latitude.so/changelog/signals-from-saved-searches
warningPage should have one primary H10https://latitude.so/changelog/cost-dashboard
warningPage should have one primary H10https://latitude.so/changelog/pii-redaction
warningTitle length should be reviewed80https://latitude.so/changelog/trace-imports
warningPage should have one primary H10https://latitude.so/changelog/trace-imports

Crawled pages

StatusTitleH1sWordsResponseURL
200AI Agent Observability & Monitoring - Latitude178679 mshttps://latitude.so/
200Pricing - AI Agent Observability - Latitude1303109 mshttps://latitude.so/pricing
200Customers \Latitude1145160 ms
200Changelog \Latitude1563199 ms
200Latitude Blog — Notes on Agent Engineering14450254 mshttps://latitude.so/blog
200Terms of Service - Latitude166841 mshttps://latitude.so/terms
200Privacy Policy - Latitude1628168 mshttps://latitude.so/privacy
200How HeyTavi centralized debugging across dozens of personalised agent deployments \Latitude11187129 ms
200Latitude Alternatives & Competitor Comparisons (2026)1546157 mshttps://latitude.so/compare
200Latitude Developer Resources — API, MCP Server, SDKs & OpenAPI Spec171690 mshttps://latitude.so/developers
200Agent Score \Latitude Changelog0559159 ms
200Turn a saved search into a signal \Latitude Changelog0262182 ms
200Cost \Latitude Changelog0281287 ms
200PII redaction \Latitude Changelog0287288 ms
200Import your traces from Langfuse, LangSmith, and Braintrust \Latitude Changelog0261289 ms

This is a bounded Scout crawl. Core Web Vitals and Lighthouse scores are not claimed unless a dedicated performance audit is connected.

22

Search Console and Analytics

First-party search and behavioral data connection state.

Modeled acquisition channels

ChannelEstimated share
direct20.4%
search5.7%
search organic5.3%
search paid0.3%
social63.7%
social organic3.7%
social paid60.0%
referrals7.5%
paid referrals0.0%
mail1.2%
gen ai1.6%
affiliate0.0%
other0.0%

First-party connections

IntegrationStatusData available after connection
Google Search ConsoleNot connectedClicks, impressions, CTR, average position, queries, pages, countries, and devices
Google AnalyticsNot connectedOrganic sessions, engagement, landing pages, conversions, geography, and devices

No first-party Search Console or Analytics numbers are shown until the site owner authorizes the corresponding Google account. Scout traffic model values above are modeled estimates, not private analytics totals.

Limits and method

23

Limitations and open questions

Known constraints and missing evidence from the collected pages.

The collected pages do not mention specific limitations or gaps. However, the pricing page indicates that the free plan has a 30-day retention limit S28, and the Pro plan has a 90-day retention limit S28. The site does not provide details on company ownership, contact information, or uptime status. The external proof search discovered a review profile, but its content was not collected.

24

Sources, method, and limitations

Evidence inventory, collection method, provider use, and constraints.

This report is based on 13 collected pages from latitude.so, including the homepage, pricing page, and blog posts. The collection used static and browser rendering rendering, with partial sitemap coverage. An external proof search was performed, but no first-party verification of external claims was obtained. The evidence catalog includes 178 items, but only a subset was used due to relevance and duplication. Limitations include incomplete coverage of the site (13 of 15 pages) and the absence of first-party customer reviews or detailed documentation.

Paid against free, in your inbox

One job at a time: the paid tools worth paying for, the free ones you can run yourself, and who should pick which.

No tracking pixels. One click to leave. We use your address to send Stack Radar and nothing else. Privacy.