Independent technical audit

parseable.com

Overall AI readiness score

A combined result across all audit signals.

Excellent

AI readiness audit: 9/27/2026Public technical data

Overall AI readiness assessment

How ready parseable.com is for AI systems

90/100

Parseable (parseable.com) received an AI-readiness score of 90/100 in an automated technical audit. llms.txt was accessible, llms-full.txt was accessible, and ai.txt was not found. The robots.txt analysis found 5 explicitly allowed and 0 blocked AI crawlers, with 3 declared sitemaps. Homepage markup completeness was 80%; Schema.org types included Organization, WebSite and 8 OpenGraph tags were detected. Results reflect the public site response observed on 2026-09-27T02:49:06.292Z.

Audit context

llms.txt is accessible and contains 2,206 tokens. An expanded llms-full.txt is also available with 14,326 tokens, giving agents more direct context. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.

robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 3. The homepage exposes Schema.org types Organization, WebSite; 8 OpenGraph tags were found and markup completeness is 80%.

The mobile Lighthouse profile adds Performance 34/100, Accessibility 98/100, Best Practices 96/100, SEO 100/100, and experimental Agentic Browsing 100/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.

Confirmed strengths

Accessible llms.txt
Expanded llms-full.txt
3 sitemap declarations
Schema.org: Organization, WebSite
Complete social metadata
Strong Google agentic signals

Priority improvements

1Reduce mobile rendering delay and main-thread work.

llms.txt tokens2,206

llms-full.txt tokens14,326

ai.txt

sitemap.xml

Google Lighthouse technical profile

A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.

Mobile · Lighthouse

Performance

Accessibility

Best Practices

100

Technical SEO

100

Agentic Browsing

What these results mean

Mobile performance is 34/100, with the largest visible content block appearing in 22.5 s and the browser main thread blocked for 920 ms. Layout shift was 0. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.

Accessibility scored 98/100, Best Practices 96/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 100/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.

Free the main thread and accelerate the first view

Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.

Reduce code that loads without helping the page

Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.

Reduce network delay

Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.

Make controls unambiguous

Give buttons and links accessible names, associate labels with fields, and use ordered headings and semantic regions. The same structure helps screen readers and software agents understand actions.

FCP18.0 s

First content

LCP22.5 s

Main content

CLS0

Layout stability

TBT920 ms

Blocking time

SI18.0 s

Visual speed

Metric glossary

FCP · First content: When the first text or image appeared on screen.
LCP · Main content: When the largest visible element in the first viewport rendered.
CLS · Layout stability: How much content shifted unexpectedly while loading; lower is better.
TBT · Blocking time: How long the browser main thread could not respond quickly to input.
SI · Visual speed: How quickly the visible viewport filled with content.

9/27/2026Lighthouse 13.5.0Mobile profile

AI readiness checks

Machine-readable files, crawler policy, discovery, and homepage markup.

llms.txt

File found and accessible

https://www.parseable.com/llms.txt

llms-full.txt

Full version is available

https://www.parseable.com/llms-full.txt

ai.txt

ai.txt file was not found

robots.txt

File found

https://parseable.com/robots.txt

Sitemap in robots.txt3

3 sitemaps found

Schema.org (JSON-LD)

Types: Organization, WebSite

OpenGraph80%

8 OG tags found

AI bot access

Based on robots.txt analysis

GPTBotAllowed

OAI-SearchBotAllowed

ChatGPT-UserNot mentioned

Google-ExtendedAllowed

ClaudeBotAllowed

Claude-SearchBotNot mentioned

Claude-UserNot mentioned

BytespiderNot mentioned

CCBotNot mentioned

PerplexityBotAllowed

Perplexity-UserNot mentioned

Sitemaps

Declared discovery routes for crawlers and agents.

https://www.parseable.com/sitemap.xml https://www.parseable.com/blog/sitemap.xml https://www.parseable.com/docs/sitemap.xml

OpenGraph tags

Social preview metadata found on the homepage.

Markup completeness: 80%

og:titleParseable | Observability infrastructure for fast growing teams

og:descriptionUnified observability platform for logs, metrics, and traces. AI-native insights, S3-native storage, SQL queries, OpenTelemetry-native, and 80x lower cost than Datadog and Splunk.

og:urlhttps://www.parseable.com

og:imagehttps://www.parseable.com/og.png

og:image:width1200

og:image:height630

og:image:altParseable | Observability infrastructure for fast growing teams

og:typewebsite

Schema.org markup

Structured entities and properties exposed on the homepage.

Types found: 2 · Properties: 10

OrganizationWebSite

nameParseable

urlhttps://www.parseable.com/

descriptionParseable is a purpose built observability data lake for agents, apps, & systems. It unifies telemetry data, keeps full-fidelity data queryable. All the data lives in open formats on object store with complete control and ownership

logohttps://www.parseable.com/logo.png

sameAshttps://github.com/parseablehq, https://x.com/parseablehq, https://www.linkedin.com/company/parseable

contactPoint{"@type":"ContactPoint","contactType":"sales","email":"sales@parseable.com"}

foundingDate2022

legalNameParseable, Inc.

inLanguageen-US

publisher{"@id":"https://www.parseable.com/#organization"}

# Parseable

> Parseable is a unified observability platform for logs, metrics, and traces. Built in Rust on Apache Parquet and object storage (S3, GCS, Azure Blob, MinIO), it delivers up to 90% data compression, PostgreSQL-compatible SQL queries, native PromQL support (Enterprise), OpenTelemetry ingestion, and AI-native features — at up to 80x lower cost than Datadog or Splunk. Deployable as a single binary on any cloud or on-premises, with no external dependencies beyond an object store.

Parseable is available in three tiers: **OSS** (AGPLv3, self-hosted, free), **Pro** ($0.37/GB, fully managed cloud, 14-day free trial), and **Enterprise** (dedicated infrastructure, BYOC, custom pricing from $999/month).

## Getting started

- [Quickstart](https://www.parseable.com/docs/get-started): Three paths — Parseable Cloud Pro (recommended), local Docker, or self-hosted production.
- [Architecture](https://www.parseable.com/docs/architecture): Single binary with Prism UI. Runs in standalone (dev) or distributed (production) mode with separate ingestor, query, indexer, and prism node roles.
- [Self-Hosted Installation](https://www.parseable.com/docs/self-hosted/installation): Kubernetes (Helm), Docker Compose, or bare metal. Distributed mode requires an object store.
- [Configuration](https://www.parseable.com/docs/self-hosted/configuration): All configuration via environment variables — storage backends, TLS, OIDC, performance tuning, distributed mode, and hot tier.

## Ingestion

- [Ingestion overview](https://www.parseable.com/docs/ingestion): HTTP(S) JSON or OTLP/HTTP. Required headers: `X-P-Stream` (dataset), `Authorization`. Max payload 10 MiB. Events staged to disk, flushed to Parquet every minute.
- [OpenTelemetry](https://www.parseable.com/docs/ingest-data/otel): Native OTLP/HTTP for logs, metrics, and traces — zero configuration.
- [Prometheus Remote Write](https://www.parseable.com/docs/ingest-data/prometheus): Ingest metrics from any Prometheus-compatible agent directly into Parseable.
- [Auto Instrumentation (Kubernetes)](https://www.parseable.com/docs/ingest-data/auto-instrumentation): PAI operator — zero-config collection of logs, metrics, traces, and events from a K8s cluster. Supports Java, Python, Node.js, .NET.
- [eBPF / Zero Instrumentation](https://www.parseable.com/docs/ingest-data/zero-instrumentation): Kernel-level observability via Tetragon — no application code changes needed.
- [AI Agents & LLMs](https://www.parseable.com/docs/ingest-data/ai-agents): Observability for OpenAI, Anthropic, LiteLLM, LangChain, LlamaIndex, AutoGen, CrewAI, and any OTel-instrumented framework. Tracks tokens, cost, latency, and reliability.
- [Telemetry Agents](https://www.parseable.com/docs/ingest-data/logging-agents): Fluent Bit, Vector, Fluentd, Logstash, Filebeat, Promtail, OTel Collector, Syslog, Log4j, Prometheus.

## Querying

- [SQL / Key Concepts](https://www.parseable.com/docs/key-concepts/query): PostgreSQL-compatible SQL via Apache DataFusion. Supports aggregate, window, and scalar functions, regex operators (`~`, `~*`, `!~`), `EXPLAIN ANALYZE`, and `?fields=true` for response metadata. Every query requires a `start`/`end` timestamp.
- [SQL Editor](https://www.parseable.com/docs/user-guide/sql-editor): In-browser editor with intelligent auto-complete, query history, saved queries, CSV/JSON export, "add to dashboard", and AI-assisted Text-to-SQL.
- [PromQL](https://www.parseable.com/docs/user-guide/promql): *(Enterprise)* Built-in PromQL engine — no separate Prometheus instance needed. Endpoints at `/prometheus/api/v1` follow Prometheus HTTP API conventions, so existing Grafana dashboards and Prometheus-compatible tooling work without changes. Supports 50+ PromQL functions (`rate`, `irate`, `increase`, `histogram_quantile`, `predict_linear`, `holt_winters`, label operations, etc.), 12 aggregation operators, all binary and set operators, vector matching, and subqueries. Integrates with Grafana via the built-in Prometheus datasource or the Parseable Grafana plugin.
- [Partitioning](https://www.parseable.com/docs/key-concepts/partitioning): Partition a dataset on a low-cardinality column to skip irrelevant data at query time. One partition column per dataset; applies to new data only.

## Explorers and UI

- [Logs Explorer](https://www.parseable.com/docs/user-guide/logs): Field-level filters, pattern detection, histogram, forecasting, group-by, SQL Editor shortcut, AI summarise, CSV/JSON export, saved views, auto-refresh.
- [Metrics Explorer](https://www.parseable.com/docs/user-guide/metrics): All metrics summary, insights tiles with aggregation toggles, raw table view, forecasting, alert creation, dashboard export.
- [Traces Explorer](https://www.parseable.com/docs/user-guide/traces): Scatter-plot duration view, trace detail with waterfall Gantt chart, span tree, SQL Editor integration, AI summarisation.
- [Dashboards](https://www.parseable.com/docs/user-guide/dashboards): Timeseries, Line, Area, Bar, Pie, Donut, Query Value, Gauge chart types. Multi-dataset tiles, drag/resize, JSON import/export.
- [Agent Observability](https://www.parseable.com/docs/user-guide/agent-observability): Unified tracing for AI agent sessions — LLM calls, tool executions, cost tracking, PII detection, SQL-native querying.
- [Errors](https://www.parseable.com/docs/user-guide/errors): Collapses OTel trace exception spans into a curated failure list with AI root-cause summaries and Keystone escalation.

## AI features

- [AI Native](https://www.parseable.com/docs/user-guide/ai-native): *(Pro/Enterprise)* Keystone Q&A (natural-language queries across datasets), dataset summarisation, Text-to-SQL. Supports OpenAI GPT and Anthropic Claude backends.
- [Alerting](https://www.parseable.com/docs/user-guide/alerting): Threshold, anomaly detection (ML), and forecasting alerts. Targets: Webhook, Slack, Alertmanager. Per-dataset, independently evaluated.

## Administration

- [RBAC](https://www.parseable.com/docs/user-guide/rbac): Five privilege levels (Admin, Editor, Writer, Reader, Ingester). Resource-scoped roles with optional tag-level filtering for Reader.
- [API Keys](https://www.parseable.com/docs/user-guide/api-keys): Scoped, role-bound keys for automation. Sent via `X-API-Key` header. Secret shown once at creation.
- [OpenID Connect](https://www.parseable.com/docs/user-guide/openid): SSO via any OIDC provider. Group-to-role mapping via ID token claims.
- [Retention](https://www.parseable.com/docs/user-guide/retention): *(Pro/Enterprise)* Per-dataset lifecycle policies, day-granularity, `delete` action.
- [Smart Cache](https://www.parseable.com/docs/user-guide/smart-cache): *(Pro/Enterprise)* Hot-tier storage on query nodes for sub-second queries. Configured via `P_HOT_TIER_DIR`. Evicts oldest files above 80% disk usage.
- [Log IQ](https://www.parseable.com/docs/user-guide/log-iq): *(Pro/Enterprise)* Auto-parses 40+ unstructured log formats (nginx, syslog, ALB, Redis, Rails, etc.) into queryable columns at ingest time.
- [Server Metrics](https://www.parseable.com/docs/self-hosted/metrics): Prometheus exposition format at `/api/v1/metrics`. Ready-made `prometheus.yml` scrape config available.
- [REST API](https://www.parseable.com/docs/api): Full programmatic access. Basic auth or API key. Default rate limit: 100 req/min/IP.

## High availability

- [High Availability](https://www.parseable.com/docs/key-concepts/high-availability): Distributed mode with independent ingestor, querier, indexer, and Prism (leader) nodes. No separate consensus layer — nodes coordinate via `NodeMetadata` in object storage. Standalone → distributed migration is one-way and automatic.

## Editions

- [OSS](https://www.parseable.com/docs/flavours/oss): AGPLv3. Unlimited ingestion, SQL, dashboards, RBAC, OIDC, threshold alerts, configurable retention.
- [Pro](https://www.parseable.com/docs/flavours/pro): $0.37/GB ingested ($29/month minimum). Up to 30 TB/month, 21-day retention, AI features (Keystone, anomaly detection, forecasting, Text-to-SQL), shared cloud infrastructure. 14-day free trial, no credit card.
- [Enterprise](https://www.parseable.com/docs/flavours/enterprise): Custom pricing from $999/month. Unlimited ingestion, dedicated infrastructure, BYOC, BYO LLM, BYO OIDC, custom partitioning, smart cache, SLA/SLO tracking, audit logging, 24×7 support. Includes PromQL engine.

## Optional: full documentation

- [llms-full.txt](https://www.parseable.com/llms-full.txt): Complete single-file documentation for deep LLM analysis and summarisation.
- [GitHub](https://github.com/parseablehq/parseable): Source code, issues, and contribution guide.
- [Docs home](https://www.parseable.com/docs): Interactive documentation site.
- [Live demo](https://app.parseable.com): Try Parseable without installing anything.

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Added 9/27/2026