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Agentic commerce

The next step from thinking to acting

Why now

What makes agentic systems transformative

A missing layer between intelligence and execution

Continuous adaptation
and improvement

Empowering both retailers
and shoppers

The next era of commerce

How to win with agentic commerce

Reasoning & contextual understanding

Goal-oriented customer assistance

Adaptive merchandising & dynamic curation

Autonomous product & style advisor

Connected
service agents

Continual learning & optimization

Technologies

Technologies that make it happen

Serve as the cognitive core of commerce agents, enabling multi-step reasoning, contextual understanding, and decision-making that mimic human judgment. They transform static interactions into dynamic, intent-driven dialogues that evolve in real time.

Power autonomous behavior by linking reasoning with action—allowing agents to plan, delegate and execute commerce workflows like personalized styling, order management and cross-channel coordination.

Ground reasoning in real-time business data such as inventory, product attributes and CRM insights, ensuring agents’ recommendations and actions are always relevant, verifiable and accurate.

Provide persistent context that allows agents to “remember” previous interactions, preferences and brand cues, building continuity across sessions and enabling more personal, anticipatory experiences.

Enable reasoning agents to act directly within enterprise systems—updating carts, checking stock, issuing returns—bridging intelligent intent with operational execution.

Feed voice, visual and behavioral signals into reasoning loops, giving agents a situational understanding of user intent and environment that supports truly adaptive interactions.

Allow agents to learn from every engagement, refining tone, accuracy and reasoning over time to deliver increasingly precise and emotionally aligned commerce experiences.

Create controlled environments for training reasoning behaviors, improving safety and reliability before deployment, ensuring agents can handle ambiguity, conflict and human nuance.

Define ethical, compliance and brand boundaries that anchor autonomous actions in trust and responsibility, ensuring every decision aligns with business principles and customer safety.

Support scalable, low-latency deployments of reasoning agents close to the customer from mobile to in-store, enabling instant responsiveness and privacy-preserving intelligence at the edge.

Reasoning-capable LLMs (e.g., GPT-4, Claude, Gemini Pro)

Agent frameworks (LangChain, AutoGen, ReAct, CrewAI)

Retrieval-augmented generation (RAG) Pipelines

Memory & context layers (Vector Databases + Knowledge Graphs)

Action orchestration & tool use APIs

Observation interfaces (Multimodal Sensors)

Reinforcement learning & feedback loops (RLHF, RLAIF)

Simulation & synthetic data generation

Governance & policy layers

Composable infrastructure (Microservices + Edge Reasoning)

Reasoning-capable LLMs (e.g., GPT-4, Claude, Gemini Pro)

Serve as the cognitive core of commerce agents, enabling multi-step reasoning, contextual understanding, and decision-making that mimic human judgment. They transform static interactions into dynamic, intent-driven dialogues that evolve in real time.

Agent frameworks (LangChain, AutoGen, ReAct, CrewAI)

Power autonomous behavior by linking reasoning with action—allowing agents to plan, delegate and execute commerce workflows like personalized styling, order management and cross-channel coordination.

Retrieval-augmented generation (RAG) Pipelines

Ground reasoning in real-time business data such as inventory, product attributes and CRM insights, ensuring agents’ recommendations and actions are always relevant, verifiable and accurate.

Memory & context layers (Vector Databases + Knowledge Graphs)

Provide persistent context that allows agents to “remember” previous interactions, preferences and brand cues, building continuity across sessions and enabling more personal, anticipatory experiences.

Action orchestration & tool use APIs

Enable reasoning agents to act directly within enterprise systems—updating carts, checking stock, issuing returns—bridging intelligent intent with operational execution.

Observation interfaces (Multimodal Sensors)

Feed voice, visual and behavioral signals into reasoning loops, giving agents a situational understanding of user intent and environment that supports truly adaptive interactions.

Reinforcement learning & feedback loops (RLHF, RLAIF)

Allow agents to learn from every engagement, refining tone, accuracy and reasoning over time to deliver increasingly precise and emotionally aligned commerce experiences.

Simulation & synthetic data generation

Create controlled environments for training reasoning behaviors, improving safety and reliability before deployment, ensuring agents can handle ambiguity, conflict and human nuance.

Governance & policy layers

Define ethical, compliance and brand boundaries that anchor autonomous actions in trust and responsibility, ensuring every decision aligns with business principles and customer safety.

Composable infrastructure (Microservices + Edge Reasoning)

Support scalable, low-latency deployments of reasoning agents close to the customer from mobile to in-store, enabling instant responsiveness and privacy-preserving intelligence at the edge.

News & insights

Research Solvd at NeurIPS 2025: Explainable AI (XAI) and Reinforcement Learning (RL) at scale
AI & data engineering
Multimodal commerce
White paper Multimodal commerce: new era of online shopping
AI & data engineering Digital experience Retail & consumer goods
Introducing Multimodal Commerce
Article Introducing multimodal commerce: The next era of customer experience
AI & data engineering Retail & consumer goods
Research GUIDE for incremental learning – Solvd at ECAI 2025
AI & data engineering
Research Classifier-free Guidance with Adaptive Scaling  – Solvd at ECAI 2025 
AI & data engineering
Research Studying the particle collisions – Solvd at ECAI 2025 
AI & data engineering
AI adoption framework
White paper Modern banking experience: A framework for AI adoption
AI & data engineering Banking, financial services & fintech
UCE
Article The business payoff of Unified Customer Experience (UCE) 
Digital experience
AI fraud
Article The $16B question: What to do about the rise of AI fraud
AI & data engineering

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