Ask your data anything.
Get governed AI answers.

Strixa connects your data, governs your metrics, and lets every team ask questions in plain English — with answers they can actually trust.

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20+ Chart & viz types Bar, line, pie, scatter, heatmap, treemap, funnel, and more
5 Steps to intelligence Connect → model → design → distribute → automate in one platform
1 Semantic layer Metrics defined once — same logic in dashboards, reports, alerts, and AI
0 Cross-tenant leaks Tenant isolation enforced at every query, service, and embed token
Product surfaces

Two ways to deliver insight — same metrics underneath

Keep exploratory dashboards and publication-grade reports separate in the navigation, so analysts and operators each get the right tool without duplicating logic.

Interactive dashboards

Drag-and-drop layouts, 20+ chart types, cross-filtering, drill paths, and alert indicators — built on semantic models so every widget stays consistent with the business layer.

  • Version history, activity, and collaboration-friendly workflows
  • Embeds and shared links for stakeholders outside the editor
  • Alert rule triggers on-view or on schedule from widget data

Paginated reports

Multi-page report builder with layout controls, rulers, header and footer, and live preview — closer to how finance and ops teams expect packaged output to look.

  • Page management: add, reorder, rename, and remove pages
  • PDF export and scheduled email subscriptions
  • Data elements from the same semantic models as dashboards
The problem with point solutions

One platform replaces six separate tools

Most analytics stacks are held together with export scripts and hope. Strixa is engineered as a single governed system — so your metrics stay consistent from ingestion to AI answer.

ETL tools Semantic layers BI dashboards Report builders AI analytics Alert & automation systems

One governed platform — connect, model, visualize, alert, and automate.

Platform

Everything between your database and your decision-makers

From ingestion to automated actions, Strixa is structured as production services with strict tenant boundaries — so you can grow usage without growing risk.

Semantic layer

Dimensions, measures, and relationships defined once. Generated SQL respects model scope so metrics stay aligned across dashboards, reports, alerts, and AI answers.

ETL pipelines & connectors

Connect databases and SaaS sources. Run incremental loads, CDC-based pipelines, and scheduled refreshes. Shape tables for analytics without leaving the platform.

Query engine

Execute governed queries against semantic models with caching and clear error paths — whether the request comes from a dashboard tile, a report data element, or an API client.

Alerts & anomaly detection

Set threshold rules or statistical anomaly detection (z-score, IQR rolling baselines) on any widget metric. Alerts fire on schedule, on view, or on refresh — with full audit trails.

Integration rules

Chain AND conditions across KPI thresholds, dataset row counts, and alert states. Trigger in-app notifications, email, webhook, or Slack — with encrypted secrets and dead-letter queues.

AI-assisted exploration

Ask in natural language against the same metrics users see in the UI. Answers stay grounded in approved model fields — not ad hoc spreadsheet logic or hallucinated aggregates.

Integrations

Connect any data source, enrich with 200+ formulas

Every major database, cloud warehouse, SaaS app, and streaming source — plus a full expression library — connected to one governed semantic layer.

50+
Native Connectors
JDBC, REST, file, streaming
200+
Formula Functions
Aggregations, window, string…
6
Connector Categories
RDBMS, warehouse, SaaS, cloud…
Live
Real-time streaming
Kafka, Kinesis, Pub/Sub
Data Connectors
Relational Databases
PostgreSQL MySQL SQL Server Oracle SQLite MariaDB
Cloud Warehouses
Snowflake BigQuery Redshift Databricks Synapse ClickHouse
SaaS & Business Apps
Salesforce HubSpot Stripe Shopify Zendesk Google Analytics Mixpanel
Cloud Storage & Files
S3 GCS Azure Blob CSV / Excel Parquet JSON
Streaming & NoSQL
Kafka Kinesis Pub/Sub MongoDB Elasticsearch Redis
APIs & Custom Sources
REST API GraphQL Webhook JDBC Custom
Formula Library
Expression Builder
200+ functions
Aggregations
SUM()AVG()COUNT()MEDIAN()PERCENTILE()
Date & Time
DATE_TRUNC()DATEDIFF()NOW()DATEADD()
String & Text
CONCAT()TRIM()REGEXP()SPLIT()INITCAP()
Math & Statistics
ROUND()ABS()FLOOR()STDDEV()VARIANCE()
Logic & Conditionals
IF()CASE()IIF()COALESCE()NULLIF()
Window Functions
ROW_NUMBER()RANK()LAG()LEAD()NTILE()
ƒx
Explore all connectors & formulas
Embed SDK

Ship governed analytics in your product

One SDK, 12+ languages, any framework. Issue a short-lived token, drop in a component, and let Strixa handle security, caching, and rendering.

Token-Based Authentication
Short-lived signed JWTs from your server — no cookies, no OAuth redirects. Rotate every 15 minutes. Zero credential exposure in the browser.
Row-Level Security (RLS)
Pass customer_id in the embed token — Strixa injects a WHERE clause into every query. Each user sees only their data.
Origin Allowlisting
Server-side validation of the iframe parent's origin. Configure trusted domains in Admin → Branding → Embed. Blocks clickjacking and unauthorized hosts.
Web Component & Framework SDKs
Use <strixa-dashboard> in any HTML page, or import typed wrappers for React, Angular, Vue, and more.
Supported languages & frameworks
JavaScript TypeScript React Angular Vue Python Ruby PHP .NET Go Swift Kotlin
View full Embed SDK docs
embed-token.ts TypeScript 
// 1. Server: issue a short-lived embed token
import { signEmbedToken } from '@strixa/server';

const token = await signEmbedToken({
  dashboard_id: 'dash_revenue_overview',
  customer_id:  req.user.customerId,  // RLS
  ttl:          900,                      // 15 min
});
res.json({ token });

// 2. Client: drop in one component (React)
import { StrixaDashboard } from '@strixa/react';

export function Analytics() {
  const { token } = useEmbedToken();
  return (
    <StrixaDashboard
      token={token}
      theme="system"
      locale="en-US"
    />
  );
}
Your Server → signEmbedToken() → JWT (15 min) → <StrixaDashboard> → User sees their data
How it works

From raw tables to automated intelligence in five moves

  1. 1

    Connect

    Connect & ingest

    Attach databases and SaaS sources. Build ETL pipelines with full, incremental, or CDC refresh modes suited to your latency SLAs.

  2. 2

    Model

    Model the business

    Declare dimensions, measures, and joins so "revenue" means the same thing on every surface — dashboard, report, alert, or AI answer.

  3. 3

    Design

    Design experiences

    Compose interactive dashboards and multi-page reports — each consuming the same semantic contracts and query engine.

  4. 4

    Distribute

    Distribute & embed

    Share, embed into customer portals, export to PDF, and schedule email subscriptions so the right people always have the latest numbers.

  5. 5

    Automate

    Monitor & automate

    Alert on threshold breaches and anomalies. Fire webhooks, Slack messages, or emails the moment chained conditions match — zero manual checks.

Security & operations

Built like infrastructure, not a spreadsheet add-on

Every persistence path is tenant-scoped in the data model. Authentication context — not URL parameters — drives which rows, workspaces, and embed origins a session can touch.

  • Isolation by default. Tenant identifiers travel on the token; services enforce them in repositories, queries, and alert evaluations.
  • Encrypted secrets. Integration rule webhook URLs, Slack tokens, and signing secrets are encrypted at rest and never logged.
  • Embed origin control. Tenant-configured allowlists restrict which domains can host embedded dashboards, enforced at the gateway.
  • Auditable services. Fastify microservices, typed validation, OpenAPI endpoints, and per-alert audit logs for every state change.
FAQ

Questions teams ask before standardizing on Strixa

How is this different from a standalone dashboard or notebook tool?

Strixa combines ETL pipelines, a governed semantic layer, dashboards, paginated reports, AI exploration, statistical alerting, and integration rules in one product. Metrics are defined upstream so downstream artifacts — and automated actions — never drift from the source of truth.

Can we separate ad-hoc analysis from formal reporting?

Yes. Dashboards and reports live in distinct areas of the product with their own builders and navigation, while both draw from the same semantic models and query paths. Analysts get interactive exploration; finance and ops teams get polished, page-formatted output.

How do alert rules and integration rules differ?

Alert rules watch a single widget metric and fire in-app or email notifications when a threshold or statistical anomaly is detected. Integration rules are more powerful: they chain multiple AND conditions (KPI thresholds, dataset row growth, linked alert states) and can trigger webhooks, Slack messages, email, or in-app actions — with encrypted secrets and automatic dead-letter logging for failed deliveries.

What ETL and data loading options does the platform support?

The dataset service supports full refreshes, incremental loads (append-only or merge by primary key), and CDC-based pipelines that track change events from source databases. Refresh schedules are configurable per pipeline with error tracking and workspace-level scoping.

What about multi-tenant or customer-facing embedded analytics?

The architecture is multi-tenant from the ground up. Landing and auth flows reflect tenant branding, embed tokens enforce origin allowlists, and row-level security scopes data access per customer — all without cross-tenant data leakage.

How does statistical anomaly detection work?

Alert rules support two statistical modes: z-score (deviation from a rolling mean) and IQR band (deviation from a rolling median). You configure the rolling window in days, minimum sample warm-up count, and sensitivity multiplier. The system stores historical samples per widget and rule, computing baselines automatically on each scheduled run.

Ready when you are

Put governed, automated analytics in front of every team

Spin up a workspace, connect a dataset, publish your first dashboard or multi-page report, configure anomaly alerts, and wire integration rules to Slack or webhooks — all on the same day.

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