Capabilities

Context Memory
Vector-Based Retrieval & Semantic State

Move beyond the limitations of finite context windows. Give your AI agents durable, institutional knowledge that grows with your business and persists across every interaction.

Why Memory Is the Real Limitation of Enterprise AI

Standard LLMs are amnesic. They reset after every session. To build true business value, AI needs to remember policies, past decisions, and user preferences.

Finite Context Windows

Even 'large' context windows are expensive and slow when filled with irrelevant documents.

Institutional Amnesia

Without memory, AI cannot learn from mistakes or adapt to changing business rules over time.

Hallucination Risk

Forcing models to 'guess' due to lack of retrieved context leads to confident errors.

Phenomeny solves this by decoupling memory from the model.

Dynamic Retrieval (RAG)

We turn your static documentation into active intelligence using advanced Retrieval-Augmented Generation.

Semantic Search

Find information by meaning, not just keywords. Matches 'how do I reset?' with 'password recovery procedures'.

Hybrid Ranking

Combines dense vector search with sparse keyword matching (BM25) for maximum retrieval accuracy.

Metadata Filtering

Filter context by date, author, or department before the vector search even begins.

Semantic State Management

Beyond documents, we track the 'state' of your business objects and workflows.

Session State

Remembers what was said 5 minutes ago in the current chat.

User State

Tracks user preferences and role-specific constraints across sessions.

Global State

Maintains organization-wide facts (e.g., 'Maintenance Mode is ON').

Workflow State

Persists the progress of multi-step agents (e.g., 'Step 3 of 5 completed').

Structured Knowledge Graphs

Connecting the dots. We map relationships between entities to understand the 'why' and 'how'.

Entity Linking

Identifies that 'Project Apollo' implies 'Q3 Deadline' and 'Engineering Team'.

Conflict Detection

Flags when a new document contradicts an established policy node.

Causal Reasoning

Helps agents understand dependencies (A must happen before B).

Ephemeral vs. Durable Memory

Smart data lifecycle management ensures the right information is kept for the right duration.

Working Memory

High-speed cache for immediate task context. Cleared post-task.

Episodic Memory

Logs of past events and interactions for historical reference.

Semantic Memory

Long-term storage of facts, definitions, and world knowledge.

Procedural Memory

Stored 'muscle memory' of how to execute specific tools or APIs.

Hyper-Personalization at Scale

Every user gets a tailored experience based on their history and role.

Adaptive Tone

Agents learn if a user prefers concise data or detailed explanations.

Role Awareness

A CFO gets financial context; a CTO gets technical context from the same query.

Proactive Context

Agents anticipate needs based on previous patterns of behavior.

Cross-Session Continuity

Pick up exactly where you left off, even weeks later or on a different device.

Universal Sync

State is synchronized across web, mobile, and API interfaces.

Context Hydration

Instantly re-loads relevant past context when a topic re-emerges.

Summary Compression

Old sessions are summarized into compact vectors to save space.

Topic threading

Automatically groups disparate conversations by subject matter.

Information Governance

Memory is powerful. We ensure it respects security boundaries.

Vector ACLs

Access Control Lists applied directly to memory chunks.

Tenant Isolation

Strict physical separation of vector indexes between customers.

Right to Forget

One-click purging of specific memories or entire user histories.

PII Redaction

Automatically detects and masks sensitive data before storage.

Performance at Scale

Sub-50ms Latency

Optimized indexing ensures retrieval doesn't slow down the chat experience.

Billion-Scale Support

Architecture tested on indices with over 1 billion vectors.

Incremental Updates

Add new documents in real-time without rebuilding the entire index.

Next steps

Ready to build memory into your AI systems?

Stop starting from zero with every interaction. Give your enterprise the memory it deserves.

Context Memory Vector-Based Retrieval & Semantic State