The Intelligence Layer for Modern Commerce
From Real-Time
Relevance to Autonomous
Enterprise Intelligence
From Real-Time
Relevance to Autonomous
Enterprise Intelligence
From Real-Time
Relevance to Autonomous
Enterprise Intelligence
TODAY: MiQ
Merchandising Intelligence
Real-time adaptation
Clickstream
Shopper session
Relevance tuning
IMPACT TODAY
+31%
Revenue Per Visitor
Search Relevance
+132% CTR
Conversion Rate
+15.2%
Time to Value
14 days
TOMORROW: GiQ
General Intelligence
Recommended action
Business signal
Projected lift
Enterprise decision support
EXPANDING TO
Marketing
Marketing
Merchandising
Merchandising
Product Buying
Product Buying
Inventory
Inventory
Promotions
Promotions
What Exists Now. What Comes Next.
From Optimization to Autonomous Decisioning
From Optimization to Autonomous Decisioning
Most commerce platforms stop at improving outputs. Malachyte is designed to evolve decision-making itself, moving from static optimization to real-time and soon autonomous intelligence.
Level 1
Rules-Based
Manual rules, segments, static logic → Requires constant tuning
Level 2
Model-Based
ML-driven, batch learning, delayed adaptation → Improves outputs, but not continuously
Level 3
Real-Time Adaptive
Continuous learning within the session → Adapts instantly to behavior
Level 4
Autonomous Decisioning
Predicts, recommends, and executes actions across the business → Optimizes outcomes without manual intervention
Most commerce platforms operate at Levels 1–2. Malachyte is built for Levels 3–4.
How Malachyte Delivers This Progression
MiQ already operates beyond traditional personalization systems by adapting in real time to behavior, context, and business priorities. Instead of relying on delayed updates or static models, it continuously refines decisions within the session.
MiQ already operates beyond traditional personalization systems by adapting in real time to behavior, context, and business priorities. Instead of relying on delayed updates or static models, it continuously refines decisions within the session.
As the platform evolves into GiQ, those same signals extend beyond the moment, supporting prediction, recommendation of actions, and ultimately autonomous decisioning across merchandising, marketing, and operations.
As the platform evolves into GiQ, those same signals extend beyond the moment, supporting prediction, recommendation of actions, and ultimately autonomous decisioning across merchandising, marketing, and operations.
Present vs Future Capabilities
Present vs Future Capabilities
Today – MiQ
Today – MiQ
Real-time semantic understanding of intent
Session-level adaptation across search and recommendations
Rapid intent detection from behavioral signals
Continuous learning within the session (no batch delays)
Shared learnings across interactions (network effect)
Tomorrow – GiQ
Tomorrow – GiQ
Multi-step reasoning across behavioral and business signals
Predictive merchandising and trend anticipation
Attribution-aware decisioning tied to business outcomes
Prescriptive recommendations for teams
Autonomous execution of repeatable decisions
Scalability & Performance
Architecture That Learns in the Moment and Over Time
Architecture That Learns in the Moment and Over Time
Short-Term Session Memory
Short-term memory captures immediate intent signals like clicks, searches, scroll depth, and product exploration
Long-Term Profile
Long-term memory preserves broader behavioral patterns, product relationships, and repeated preference signals across time.
Unified Context Vector
These are fused into a context vector that updates continuously, allowing the system to respond with both speed and continuity
Short-Term Session Memory
Short-term memory captures immediate intent signals like clicks, searches, scroll depth, and product exploration
Long-Term Profile
Long-term memory preserves broader behavioral patterns, product relationships, and repeated preference signals across time.
Unified Context Vector
These are fused into a context vector that updates continuously, allowing the system to respond with both speed and continuity
Short-Term Session Memory
Short-term memory captures immediate intent signals like clicks, searches, scroll depth, and product exploration
Long-Term Profile
Long-term memory preserves broader behavioral patterns, product relationships, and repeated preference signals across time.
Unified Context Vector
These are fused into a context vector that updates continuously, allowing the system to respond with both speed and continuity
Algorithmic Foundation
Malachyte is built from the ground up for modern AI. The system combines transformer-based models, vector similarity search, and multi-objective optimization to interpret behavior and make decisions in real time. Unlike legacy platforms that rely on rules or static segments, Malachyte is designed for streaming contextual data and continuous learning. Teams don’t need to hand-tune algorithms—instead, they define high-level business goals, and the system dynamically optimizes toward them.
Scalability & Performance
Real-Time Continuous Learning at Any Scale
Real-Time Continuous Learning at Any Scale
Built for streaming data, high concurrency, and zero degradation under peak demand.
Instant Adaptation
Updates recommendations and search results with every interaction. Models adapt within the same session.
<50ms
response time
Cloud-Native Architecture
Built for horizontal scaling and high concurrency. No slowdowns under peak demand.
99.99%
uptime SLA
Global Scale
Handles high query volumes across regions. Edge delivery ensures low latency everywhere.
10M+
queries/day capacity
Integration & Data Architecture
Fast to Deploy.
Built for Privacy.
Fast to Deploy.
Built for Privacy.
Malachyte integrates quickly with modern commerce platforms while operating entirely on first-party behavioral data.
Privacy-First
by Design
No Third-Party Cookies
Compliant with GDPR, CCPA, and evolving privacy standards
No PII Usage
Enhances your existing data without requiring heavy integration or external enrichment
Plug-and-Play
Deployment
Plug-and-Play
Deployment
Designed for rapid integration with platforms like Shopify and modern commerce stacks.
INTEGRATION TIMELINE
Days
Initial signal capture & baseline relevance
2 Weeks
Full experience rollout
4–6 Weeks
Measurable performance lift
Compounding Intelligence
A System That Gets Better With Every Interaction
A System That Gets Better With Every Interaction
Malachyte improves continuously as it learns from real behavior, creating a widening performance advantage over time.
Most personalization platforms require constant tuning to maintain performance. Malachyte is designed differently.
Every search, hover, scroll, click, and conversion feeds back into the system. As the platform processes more interactions, it improves how it interprets intent, ranks products, and surfaces recommendations — better decisions lead to stronger engagement, which generates more high-quality signals.
This creates a compounding learning loop where performance improves automatically, without relying on manual rule updates. The same loop that powers MiQ today becomes the foundation for GiQ's predictive and autonomous capabilities.
Our Vision
Our Vision
One Platform,
Many Applications
One Platform,
Many Applications
The same intelligence layer powers discovery today, and expands into decision-making across categories, teams, and markets over time.
01
Apparel & Fashion
Personalized outfit recommendations, style prediction
02
Toys & Kids Products
Smart search by age, dynamic costume bundling
03
Beauty & Skincare
Personalized regimen suggestions, shade matching
Personalized regimen suggestions, shade matching
04
Footwear
Style terminology, comfort vs fashion preferences
05
Home Goods & Furniture
Style-based search, room-based recommendations
Style-based search, room based recommendations
Malachyte is not limited to a single use case or vertical. Its core architecture adapts across complex catalogs, changing shopper behaviors, and different business models.
What begins as improved search, discovery, and recommendations evolves into a broader decisioning layer used across merchandising, CRM, paid media, and planning. The same system that optimizes a shopper’s experience can guide inventory strategy, campaign execution, and business prioritization.
One platform. One intelligence layer. Expanding value across the organization.
Expansion Across Teams
Expansion Across Teams
Real-time intelligence, applied across the enterprise.
Executive Insight
Strategic decisioning & performance intelligence
Inventory
Stock optimization
& allocation
Product Buying
Demand forecasting & assortment
Merchandising
Product discovery & search
Product discovery & search
Marketing
Campaign optimization & audience targeting