Side by Side
8 head-to-head breakdowns to help you decide.
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AI Agents vs. RPA
How AI agents compare to Robotic Process Automation, when to use reasoning-based agents and when to keep rule-based bots.
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AI Agents vs. Zapier/Make
When to use AI agents and when to keep your Zapier/Make automations, the flexibility-complexity trade-off for operational automation.
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Build In-House vs. Embed Partner
The real trade-offs between hiring an internal AI team and embedding an implementation partner, cost, speed, risk, knowledge retention, and what happens after.
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Business-as-Code vs. Traditional Consulting
How Business-as-Code differs from traditional consulting approaches to AI implementation, why executable artifacts beat strategy decks.
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Multi-Agent (Deep Agents) vs. Single Agent
When a single AI agent is enough and when you need multi-agent orchestration, the architecture decision that determines your AI system's capability ceiling.
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MCP vs. REST
How the Model Context Protocol compares to REST APIs for connecting AI systems to business tools, the architectural shift from human-designed APIs to agent-designed protocols.
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NimbleBrain vs. Accenture
How NimbleBrain's embed model compares to Accenture's AI practice, team size, timeline, deliverables, cost, and what you own when it's over.
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Open Source vs. Vendor Platform
The trade-offs between open-source AI infrastructure and vendor platforms, control, cost, security, support, and what happens when the vendor changes direction.