FullStory (with AI)

FullStory: Agentic AI & Behavioral Data Orchestration Review

As of January 2026, FullStory has transitioned from a monitoring tool to an active AI-analytical hub. The core architecture centers on the Fullcapture™ engine, which logs a continuous stream of DOM mutations. This telemetry is then processed by StoryAI, an orchestration layer that leverages advanced LLMs to provide real-time reasoning over unstructured behavioral data 📑.

Model Orchestration & AI Architecture

The system utilizes Google Gemini 2.0 (and 1.5 Pro for deep historical analysis) as its primary reasoning engine. StoryAI manages the injection of session context into the model's prompt window, ensuring high-fidelity grounding.

• Operational Scenario: Contextual Session Ingestion & LLM Synthesis:
  Input: Stream of serialized DOM mutations and network HAR logs (sanitized via Header Privacy Rules) 📑.
  Process: The StoryAI Orchestrator vectorizes interaction sequences, identifies 'Struggle Signals', and sends a structured prompt to the Gemini-Pro inference cluster [Inference].
  Output: An 'Ask StoryAI' narrative summary that correlates UI bugs with quantified business loss in plain language 📑.
• Hybrid Logic Layer: Combines deterministic 'Heuristic Struggle' detection (e.g., rage clicks) with probabilistic AI intent prediction to reduce the false-positive rate of automated alerts 🧠.

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Performance & Resource Management

FullStory utilizes an asynchronous capture script (fs.js) that offloads mutation serialization to **Web Workers** to maintain a healthy Interaction to Next Paint (INP) score 📑.

• Privacy & Edge Masking: 2026 Header Privacy Rules allow teams to define exclusion patterns for HTTP headers globally. This prevents the ingestion of sensitive session tokens or PII at the network level 📑.
• Storage Locality: FullStory manages a persistence layer with dedicated regional clusters (NA1, EU1). While storage is managed, data is logically isolated per tenant within Google Cloud's distributed infrastructure 📑.

Evaluation Guidance

Technical evaluators should verify the following architectural characteristics:

• Interaction to Next Paint (INP) Impact: Benchmark the fs.js Web Worker overhead on mobile devices with limited CPU cores to ensure capture does not trigger UI jank [Inference].
• AI Grounding Fidelity: Test 'Ask StoryAI' with complex multi-page funnels to ensure the LLM correctly interprets cross-page state transitions without hallucinating intent 🧠.
• Data Residency for AI: Confirm that Gemini-based sub-processing remains within the EU data boundary for EU1-hosted accounts, as cross-border AI inference is a critical compliance risk in 2026 🌑.
• Header Privacy Granularity: Validate that the new January 2026 privacy rules can target specific JSON keys within the request body, not just top-level headers 🌑.