Built on a complete data model

16-module Truth Layer. Data model complete from day one, UI minimal from day one.

Most analytics platforms add features by adding tables. Gurulu starts with the canonical data model and grows the UI around it.

متاح الآن

مباشر في النسخة التجريبية اليوم

ما يمكنك استخدامه الآن — الأربعة الأساسية، القنوات الأربع، الخصوصية، والملخّص اليومي بالذكاء الاصطناعي.

Core four, always on

The four pillars of the Truth Layer

Identity, registry, health and attribution are mandatory in every tier and every workspace. They are how Gurulu earns the word truth.

Identity engine

مباشر

Explainable merge with a four-tier confidence ledger. Every join, split and reassignment is recorded with the evidence that triggered it. Reversible by design.

  • Four-tier confidence: deterministic, probabilistic, AI-suggested, manual
  • Reversible merge ledger with full audit trail
  • Cross-domain resolution — open to all

Event registry

مباشر

Events are typed contracts. Schemas live in the registry, ingestion enforces them, so drift becomes impossible. SDKs and AI agents generate code against the registry — no freestyle event names.

  • Source-of-truth schema with validation gate at ingestion
  • Accept / Warn / Quarantine / Reject ingestion outcomes
  • Code-gen typed SDKs for every workspace

Event health

مباشر

Multi-selector matchers + 5-layer fail-safe + ML anomaly detection. Tracking regressions are caught before the dashboard lies — usually within minutes of deploy.

  • Multi-selector resilience for autocapture rules
  • ML anomaly detection per event / property / cohort
  • CAPI dedup so downstream destinations stay clean

Attribution engine

مباشر

Customer-defined policy. Pick your model, mix multiple models side by side, and see the full trace behind every credited touchpoint. No black-box numbers, ever.

  • Multi-model: last-touch, first-touch, linear, time-decay, position-based
  • Customer-defined attribution policy per workspace
  • Full provenance trace for every conversion

Four channels, four jobs

Observation, tagging, verification and contract — never blurred

Most platforms hide one SDK behind every feature. Gurulu separates the four jobs on purpose — every channel has a single, narrow responsibility.

01 · Script

مباشر

Observe

Browser autocapture only. Records raw signals — never invents outcomes, never makes up event names.

Package: @gurulu/web

02 · Playground

مباشر

Tag

Heap-style visual picker writes semantic rules into the registry. No events are created here — only rules that match observed signals to typed contracts.

Package: @gurulu/playground

03 · SDK

مباشر

Verify

Server-side outcome verification. Conversions, refunds, signups — all backend-bound so they can't be spoofed. Web identify/track is registry-bound too.

Packages: @gurulu/node + @gurulu/web

04 · Agent · CLI · MCP

مباشر

Contract

AI authors against the registry. Types are code-generated, freestyle event names are blocked at CI. The agent never invents a new event without a contract.

Packages: @gurulu/cli + @gurulu/mcp-server

أدوات المطوّرين

يعمل حيث تكتب الشيفرة

من المتصفح إلى الطرفية إلى محرّر الذكاء الاصطناعي — كل أداة تؤدي مهمة واحدة وتحترم العقد.

خادم MCP · Cursor · Claude Code · Lovable

مباشر

محرّر الذكاء الاصطناعي يكتب وفق الـ registry

يربط خادم MCP مساعدك الذكي بسجلّ الأحداث. يَسرد العميل ويبحث ويتحقّق من أي حدث جديد عبر validate_event قبل إرساله — ولا يمكنه اختلاق أسماء عشوائية. عقدك صامد في عصر الذكاء الاصطناعي أيضًا.

  • يقرأ الـ registry: list / search / get event
  • يتحقّق أولًا: add_event ← validate_event
  • بلا أسماء عشوائية — يتبع العقد
الوثائق →
claude mcp add gurulu -- npx -y @gurulu/mcp-server

SDK · ويب (@gurulu/web)

مباشر

المتصفح: التقاط تلقائي + identify/track. بلا تبعيات، ~8 ك.ب.

gurulu.track('signup_completed', { plan: 'pro' })
الوثائق →

SDK · خادم (@gurulu/node)

مباشر

الخادم: نتائج موثوقة + مساعدات webhook لـ Stripe/Shopify.

await gurulu.track('purchase_completed', { amount: 149 })
الوثائق →

Playground

مباشر

نقر واختيار بأسلوب Heap. يضيف قواعد إلى الـ registry بلا شيفرة.

الوثائق →

CLI (@gurulu/cli)

مباشر

init / pull / push / validate / doctor. توليد شيفرة أحداث مُنمّطة.

gurulu pull   # typed events → code-gen
الوثائق →

Three event classes

Interaction, intent and outcome — split from day one

Mixing browse, signal and conversion in one table is the original sin of product analytics. Gurulu separates them in the schema, not just in queries.

Class 01

مباشر

Interaction

Clicks, scrolls, views — the raw stream of human behavior. High volume, low semantics.

Class 02

قريبًا · المرحلة 2

Intent

Inferred signal — a search query, a hesitation, an abandoned cart. Modeled in Phase 2+ with consent-aware enrichment.

Class 03

مباشر

Outcome

Backend-verified result — a purchase, a refund, a paid signup. The only class that can credit attribution.

Privacy by default

EU-native, compliance-first, multi-tenant safe

Privacy is enforced in the data model, not bolted on. Every row knows its consent state and its tenant — no leaks possible.

مباشر

EU residency default

Hosted in EU data centers with automatic failover. No US data transfer needed for GDPR-bound customers.

مباشر

4-category GCM v2

Google Consent Mode v2 wired into every event — analytics, advertising, personalization and security consent surface independently.

مباشر

DSR-ready exports

GDPR / CCPA / KVKK subject-access and erasure requests resolve through a single API. Audit trail included.

مباشر

Tenant isolation + RLS

Postgres row-level security on every table, ClickHouse partition-per-tenant. Cross-tenant queries are physically impossible.

AI layer

AI that explains itself — and never sees raw PII

Pseudonymize everything before it touches a model. Show the prompt, the citations and the confidence behind every AI suggestion.

مباشر

Morning summary

Phase 1 minimum: every workspace gets a daily digest of what changed, what broke and what to investigate. Cited back to the source events.

قريبًا · المرحلة 2

Intent inference

Phase 2+: classify raw behavior into intent classes (researching, comparing, ready-to-buy). Consent-aware and pseudonymized end-to-end.

قريبًا · المرحلة 3

Advanced reasoning

Phase 3+: cross-event causal reasoning, hypothesis generation, experiment suggestion. Always paired with provenance and confidence.

Multi-model AI pipeline · region-aware automatic fallback

ما التالي

خارطة الطريق

مُعلَّمة بوضوح، ولم تصل بعد. لكل مرحلة تعريف “مكتمل” علني.

Phased delivery

From Phase 0 to Phase 5 — the public roadmap

MVP is Phases 0–3 (~9–12 months). Phases 4 and 5 are post-MVP. Every phase has a public Done definition.

  1. 00
    Phase 0 — FoundationAuth, storage, observability, consent. 4 modules.
  2. 01
    Phase 1 — Core four + data flow + 4 channels + UIBeta opens here. 16 modules total.
  3. 02
    Phase 2 — Intent inference + integrationsIntent class lights up, CAPI destinations expand.
  4. 03
    Phase 3 — Advanced attribution + monetizationOfficial launch + paid pricing turns on.
  5. 04
    Phase 4 — Cross-tenant intelligenceBehavioral benchmarks opt-in for the Pay-as-you-go tier.
  6. 05
    Phase 5 — Native observability platformGurulu monitoring Gurulu — our own native observability platform.
Features — Gurulu Truth Layer