>initializing a.gentic system...
activate agentic commerce
>Re-architect your brand for the agent economy
a.gentic system
>loading ai infrastructure components...
>initializing pinecone vector database...
>connecting to neo4j graph database...
>establishing timescaledb metrics storage...
>loading video assets for vectorization...
>spinning up mcp server...
>loading customer data vectors...
>deploying cro agents...
>preparing agentic ads...
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a.genticv1.0.0
>system ready
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system message
>the future belongs to ai-native brands
>a.gentic transforms e-commerce brands by building custom ai capabilities directly into your infrastructure — not locked in someone else's saas platform. we create your ai-native nervous system while traditional software vendors are still selling you yesteryear's crud forms with a fresh coat of paint. the agent economy won't be kind to brands waiting for quarterly feature releases or trapped in rigid workflows. the future belongs to brands that deeply integrate with ai, not those still clicking through the same old interfaces while the world moves on.
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>white-labeled infrastructure that transforms customer experiences
feature_1
>agentic ad operations at scale
>vectorize your existing video assets in aws s3 and pinecone to create a reusable scene library. ai agents can instantly search, combine, and repurpose these vectors to generate thousands of targeted ad variations. cuts agency costs. scales your campaign reach.
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feature_2
>your very own mcp server
>implement model context protocol servers that connect your pinecone vectors and neo4j databases directly to ai assistants like claude and chatgpt. allows customers to interact with (and soon buy) your brand's products through any ai interface they prefer.
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feature_3
>hyper-personalized targeting
>deploy customer profiles and product information into your own pinecone instance to match people with exactly the right messages.
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feature_4
>autonomous conversion optimization
>store user session recordings in pinecone for pattern matching, map interaction flows in neo4j, and track metrics in timescaledb. enables ai agents to analyze behavior patterns, identify friction points, and autonomously implement conversion improvements without waiting for human analysis.
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feature_5
>customer journey graph database
>upgrade to neo4j graph database to track complex relationships between customers, products purchased, and marketing message responses.
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feature_6
>experiential product discovery
>vector search enables natural language product exploration. powers sophisticated chatbots and virtual try-ons.
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feature_7
>rapid packaging development
>store design concepts and feedback in vector databases to dramatically accelerate iteration and cut development time from weeks to days.
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feature_8
>product formulation intelligence
>leverage neo4j to map complex ingredient interactions, regulatory requirements, and clinical test results in a graph database. enables ai to rapidly identify compatible ingredients, predict product benefits, and recommend formula recipes. reduces research time from weeks to days. cuts raw material costs.
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>the a.gentic implementation process
process execution
>step 1: infrastructure setup
$we configure vector and graph databases on your servers
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>step 2: data migration
$your product catalog, customer data, and brand assets are vectorized
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>step 3: agent development
$on-demand custom agents are created to handle specific business functions
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>step 4: knowledge transfer
$your team receives full documentation and training
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>step 5: complete handover
$you gain 100% ownership of your infrastructure and data with no vendor lock-in. flexible options for ongoing support, agent subscriptions, or enhancements as your needs evolve
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