Why founders are hunting for alternatives

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What is Decentralized AI?

A catch‑all term for architectures where data, models, or compute stay distributed instead of flowing into one hyperscale cloud. Popular flavors include:

• Federated learning—models train on‑device or on‑prem and share gradients.
• Compute marketplaces—spare GPUs on PCs or edge devices rent themselves out .
• Blockchain‑AI hybrids—shared ledgers track model ownership; the market hits $0.7 B in 2025 (CAGR 23 %)

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How decentralization tackles your pain points

Enterprise platforms are already moving

• Salesforce Agentforce – 1 M autonomous support conversations, 84 % resolved by bots and a 5 % drop in case volume. Shows agents can run at scale when integrated with existing CRM data
• Microsoft Dynamics 365 – new Model Context Protocol (MCP) servers let partners plug in AI agents without brittle ETL work, signalling a shift toward “bring‑your‑own‑agent” architectures
• Workday Agent Gateway – an Agent System of Record that treats AI agents like employees and lets partners (AWS, Google Cloud, Accenture) register their own agents securely

For founders, that means decentralized or edge‑trained models can be surfaced inside tools your teams already live in—no forklift migration required.

Quick‑start roadmap (zero jargon)

1. Map data gravity & compliance hotspots
   Identify which datasets can’t leave on‑prem or a specific region.
2. Pick one “edge‑ready” use case
   e.g. predictive maintenance on IoT devices or local‑first customer insights.
3. Prototype with federated frameworks
   Flower’s quick‑start gets a PoC running in < 1 day; no Kubernetes mastery needed.
4. Tap compute marketplaces for bursts
   Rent verified community GPUs for training spikes—pay only for minutes used.
5. Integrate via platform APIs
   Publish results back to Salesforce dashboards, Dynamics flows or Workday reports using their native agent hooks.
6. Measure & iterate
   Track cost per inference, latency and compliance score—not just model accuracy.

Where Proso fits in

As a tech‑consulting partner certified across Salesforce, Microsoft Dynamics and Workday, Proso can:

• Run a one‑week discovery sprint to surface your highest‑ROI decentralized use cases.
• Stand up a federated learning sandbox (Flower or PySyft) hosted in your cloud or on‑prem lab.
• Wire the outputs into your existing CRM/ERP via MCP agents or Workday Agent Gateway adapters.
• Provide managed MLOps so your team focuses on products, not pipelines.

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Key takeaways

• Practical – Decentralized AI is no longer a R&D toy; enterprise platforms now expect agent plug‑ins.
• Cost‑smart – Offload training to community GPUs and cut cloud bills fast.
• Privacy‑first – Keep customer data in the region while still benefiting from network effects.
• Actionable – Start small: one use‑case, one framework, measured results.

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Ready to explore your first decentralized AI pilot? Let’s talk.

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