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Latent-Sense Technologies
The Proof-of-Value (PoV) program is designed and run by a dedicated team of AI scientists, engineers, and enterprise-grade reasoning experts from Latent-Sense Technologies. You'll gain direct access to the minds behind our neuro-symbolic platform and AI ecosystem.
In this program, we offer a rare level of expertise that is geared towards establishing long term partnerships through onboarding select and reasoning-ready enterprises into:
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Hybrid neuro-symbolic reasoning architectures
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Reasoning maps,
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Multi-agent swarms orchestrators
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Benchmarking protocols for reasoning coherence
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Governance tools via synthetic detection and PII control
Pricing note: This program is customized depending on your organization’s size and use case complexity. Full pricing and structure will be determined upon consultation with interested parties.
Why This Program—and Why Now?
The AI race is on—but are you betting on the right kind of AI for your enterprise? Are you investing significant capital in AI and without diligence and proof of value?
Today’s large language models (LLMs) are powerful for tasks that have to do with language generation, but are inherently limited in language understanding and reasoning over complex knowledge in unstructured data. They generate fluent text without real understanding, traceability, or consistency. This introduces risks such as hallucinations, regulatory non-compliance, lack of explainability, and data misuse. Many organizations, at this point, are under pressure to make AI trustworthy, auditable and transparent.
To stay competitive, enterprises need AI that executes on structured reasoning.
This isn’t about demos.
It’s about proof of value on your data, for your use case.
We will help your organization move beyond black-box generative models into structured, auditable, and orchestrated reasoning systems that deliver lasting value.
What You'll Learn and Build
Over the course of the program, your team will receive a guided experience that will explore five critical dimensions of next-generation AI systems:
Design of Reasoning Infrastructures
Build reasoning foundations using ReX and rxMaps—our neuro-symbolic reasoning systems that preserves context, traceability, and logic across documents and agent sessions.
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Orchestrating Reasoning Agents (Swarms)
Deploy modular reasoning agents that reason over complex documents and written corpora. Learn how to make multi-agent swarms simulate rigorous, expert-like analysis at scale.
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Deployment of Reasoning Services
Go from theory to execution, and use our APIs, MCP, SDKs and orchestrator to integrate and trigger reasoning agents across your data pipelines.
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Benchmarking Reasoning Agents and Swarms
Use our proprietary methods to measure reasoning quality using advanced benchmarks—from logical coherence and contradiction detection to causal inference and collaborative performance.
Governance and Sustainability
Ensure AI trust and longevity with built-in tools for privacy preservation (ReDid) and synthetic content detection (AiTD).
This isn’t about demos. It’s about proof of value—on your data, for your use case. We will help your organization move beyond black-box generative models into structured, auditable, and orchestrated reasoning systems that deliver lasting value.
What You’ll Walk Away With
By the end of the program, your team will have:
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A deployed reasoning pipeline using your own documents and data
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Benchmarked performance of single agents and swarms
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Persistent portable and interoperable rxMap for domain knowledge
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Validated use case report and roadmap for enterprise-scale rollout
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A comprehensive governance checklist and reasoning audit trail
You’ll walk away with evidence and clarity on how reasoning AI can fit your enterprise AI needs.
Who Should Join?
This program is for forward-thinking teams across:
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AI, Data & Innovation Units — looking to operationalize reasoning across their enterprise (e.g. legal, healthcare, security, compliance, insurance, etc)
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CIOs, CTOs & Heads of Strategy — exploring scalable, explainable AI infrastructure
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Compliance, Risk & Legal — needing auditability and structured reasoning anchored validation
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Product & Engineering Teams — aiming to embed AI auditability and structured reasoning into their enterprise knowledge workflows