Audit technique indépendant

parseable.com

Score global de préparation IA

Résultat combiné de tous les signaux de l’audit.

Excellent

Audit de préparation IA: 27/09/2026Données techniques publiques

Évaluation globale de préparation IA

Niveau de préparation de parseable.com pour les systèmes d’IA

90/100

Parseable (parseable.com) a obtenu 90/100 lors de l’audit technique automatisé de préparation à l’IA. llms.txt était accessible, llms-full.txt avait un format valide et ai.txt était introuvable. L’analyse de robots.txt a trouvé 5 robots IA explicitement autorisés, 0 bloqués et 3 sitemaps déclarés. La complétude du balisage de la page d’accueil atteint 80% ; types Schema.org détectés : Organization, WebSite. Balises OpenGraph détectées : 8. Les résultats correspondent aux réponses publiques observées le 2026-09-27T03:45:09.364Z.

Contexte de l’évaluation

L’audit combine les fichiers lisibles par les machines, les règles des robots, les sitemaps et le balisage de la page d’accueil. llms.txt est accessible et contient 2 206 jetons.

robots.txt est disponible ; robots IA bloqués : 0. Sitemaps déclarés : 3. Types Schema.org : Organization, WebSite.

Profil Lighthouse mobile : performance 34/100, accessibilité 98/100, SEO 100/100.

Points forts confirmés

llms.txt est accessible
llms-full.txt est disponible
3 sitemap(s) déclaré(s)
Schema.org : Organization, WebSite

Améliorations prioritaires

1Maintenir les fichiers et le balisage à jour après chaque modification du site.

Jetons llms.txt2 206

Jetons llms-full.txt14 326

ai.txt

sitemap.xml

Profil technique Google Lighthouse

Une mesure Lighthouse mobile. La catégorie expérimentale Agentic Browsing est présentée séparément et ne remplace pas le score global de LLMSMap.

Mobile · Lighthouse

Performance

Accessibilité

Bonnes pratiques

100

SEO technique

100

Agentic Browsing

Interprétation des résultats

La performance mobile est de 34/100 ; le plus grand contenu visible est apparu en 22.5 s et le thread principal a été bloqué pendant 920 ms. Le décalage de mise en page est de 0. Les tâches longues retardent les actions des utilisateurs et des agents de navigateur.

Accessibilité : 98/100, bonnes pratiques : 96/100, SEO technique : 100/100. La catégorie expérimentale Agentic Browsing atteint 100/100 et reste distincte du score global de LLMSMap.

Libérer le thread principal et accélérer le premier écran

Découpez les longues tâches JavaScript, différez les scripts et styles non critiques et réduisez les chaînes de requêtes bloquantes.

Réduire le code chargé inutilement

Supprimez le CSS et le JavaScript inutilisés, chargez les widgets lourds à la demande et limitez les scripts tiers.

Réduire la latence réseau

Améliorez la réponse du serveur, retirez les redirections inutiles et utilisez la compression et le cache.

Rendre les commandes explicites

Nommez clairement boutons, liens et champs et structurez les titres et régions sémantiques.

FCP18.0 s

Premier contenu

LCP22.5 s

Contenu principal

CLS0

Stabilité visuelle

TBT920 ms

Temps de blocage

SI18.0 s

Vitesse visuelle

Glossaire des métriques

FCP · Premier contenu: Moment où le premier texte ou la première image apparaît.
LCP · Contenu principal: Moment où le plus grand élément visible est affiché.
CLS · Stabilité visuelle: Déplacements inattendus pendant le chargement ; une valeur basse est préférable.
TBT · Temps de blocage: Durée pendant laquelle le thread principal ne pouvait pas répondre rapidement.
SI · Vitesse visuelle: Vitesse à laquelle la zone visible s’est remplie de contenu.

27/09/2026Lighthouse 13.5.0Profil mobile

Vérifications de préparation IA

Fichiers lisibles par les machines, règles des robots, découverte et balisage de la page d’accueil.

llms.txt

Fichier trouvé et accessible

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

llms-full.txt

La version complète est disponible

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

ai.txt

Le fichier ai.txt est introuvable

robots.txt

Fichier trouvé

https://parseable.com/robots.txt

Sitemap dans robots.txt3

3 sitemaps trouvés

Schema.org (JSON-LD)

Types : Organization, WebSite

OpenGraph80%

8 balises OpenGraph trouvées

Accès des robots IA

D’après l’analyse de robots.txt

GPTBotAutorisé

OAI-SearchBotAutorisé

ChatGPT-UserNon mentionné

Google-ExtendedAutorisé

ClaudeBotAutorisé

Claude-SearchBotNon mentionné

Claude-UserNon mentionné

BytespiderNon mentionné

CCBotNon mentionné

PerplexityBotAutorisé

Perplexity-UserNon mentionné

Sitemaps

Parcours de découverte déclarés pour les robots et les agents.

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

Balises OpenGraph

Métadonnées d’aperçu social détectées sur la page d’accueil.

Complétude du balisage: 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

Balisage Schema.org

Entités et propriétés structurées exposées sur la page d’accueil.

Types : 2 · Propriétés : 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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Ajouté 27/09/2026