Fusion Agentic Applications vs Adept

Detailed side-by-side comparison to help you choose the right tool

Fusion Agentic Applications

Business AI Solutions

Oracle AI agents embedded natively in Fusion Cloud Applications (ERP, HCM, SCM, CX) that automate complex business processes using generative AI, pre-built agent workflows, and Oracle Cloud Infrastructure.

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Adept

πŸ”΄Developer

Business AI Solutions

Adept AI licenses its ACT-1 Action Transformer technology to enterprise partners, enabling them to build AI agents that visually control any computer software using natural language commands. Through its partnership model, Adept provides screen-reading AI models, proprietary training datasets, and technical consultation for building custom agentic automation solutionsβ€”offering an alternative to traditional RPA platforms for organizations with complex, multi-application workflows.

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Feature Comparison

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FeatureFusion Agentic ApplicationsAdept
CategoryBusiness AI SolutionsBusiness AI Solutions
Pricing Plans10 tiers6 tiers
Starting PriceContact Sales
Key Features
  • β€’ 50+ pre-built AI agents spanning ERP, HCM, SCM, CX, and EPM modules
  • β€’ Native access to live Fusion Applications transactional data without integration middleware
  • β€’ Natural language interaction for initiating and monitoring multi-step workflows
  • β€’ Visual screen understanding and automation
  • β€’ Natural language workflow execution
  • β€’ Cross-application automation capabilities

Fusion Agentic Applications - Pros & Cons

Pros

  • βœ“Agents are embedded directly inside Fusion ERP, HCM, SCM, and CX, so they inherit the application's existing security model, role-based access, and audit trail rather than requiring a separate integration layer.
  • βœ“Many agent capabilities are delivered as part of the standard Fusion subscription and quarterly update cycle, which lowers the procurement and change-management overhead compared to standing up a third-party AI platform.
  • βœ“Built on Oracle Cloud Infrastructure with Oracle's Generative AI service, giving enterprise customers data residency, tenancy isolation, and a choice of foundation models (Cohere, Llama) hosted within OCI.
  • βœ“Pre-built, process-specific agents (e.g., supplier recommendations, expense auditing, candidate screening, contract analysis) reduce the amount of prompt engineering and custom development required to get value.
  • βœ“Native access to Fusion transactional data means agents can take real actions β€” posting journals, updating records, routing approvals β€” instead of just generating text suggestions a human must re-key.
  • βœ“Aligned with a vendor-native strategy that is a natural fit for organizations already standardizing on Oracle Fusion, avoiding the licensing and integration fragmentation of multiple AI vendors.

Cons

  • βœ—Value is largely confined to organizations already running Oracle Fusion Cloud Applications β€” there is little benefit for shops on E-Business Suite, JD Edwards, PeopleSoft, or non-Oracle ERPs.
  • βœ—Customers are tied to Oracle's release cadence and roadmap for which agents exist; if a desired agent isn't on the roadmap, building a custom equivalent requires OCI Generative AI skills and Fusion extensibility expertise.
  • βœ—Total cost of ownership can be opaque because agent functionality is bundled across Fusion subscriptions, OCI Generative AI consumption, and sometimes additional SKUs, making it harder to forecast spend than a flat per-seat AI add-on.
  • βœ—Oracle's published documentation about which specific agents are generally available versus in controlled release is less transparent than competitors like Microsoft and Salesforce, requiring direct engagement with Oracle to confirm scope.
  • βœ—Mature deployment typically requires Oracle or partner consulting services, which can extend time-to-value for organizations expecting an out-of-the-box, switch-on experience similar to a SaaS copilot.

Adept - Pros & Cons

Pros

  • βœ“Works with any desktop or web application without requiring API integrations - ideal for legacy systems and custom enterprise software
  • βœ“Natural language interface makes automation accessible to non-technical business users without requiring Python, JavaScript, or RPA scripting knowledge
  • βœ“Advanced reinforcement learning adaptation handles interface changes and unexpected scenarios, reducing the 30-40% maintenance overhead typical of traditional RPA deployments
  • βœ“Backed by $415M in funding with founding team including Ashish Vaswani (transformer architecture co-inventor) and former Google/OpenAI research leads
  • βœ“ACT-1 model can execute multi-step workflows spanning 10+ applications in a single natural language command, eliminating manual context switching
  • βœ“Enterprise-grade partnership model provides deep customization and dedicated technical consultation unavailable from off-the-shelf RPA vendors

Cons

  • βœ—Partnership-only access model with no self-service signup or public availabilityβ€”requires direct enterprise sales engagement and significant upfront investment
  • βœ—No transparent pricing published; licensing fees, professional services, and ongoing consultation costs are negotiated per partnership
  • βœ—Requires extensive screen access permissions that may conflict with zero-trust security policies and SOC 2/HIPAA compliance frameworks
  • βœ—Following 2024 strategic shift, key talent moved to Amazonβ€”raising questions about long-term product roadmap continuity for partners
  • βœ—Visual-only automation cannot handle command-line interfaces, headless servers, or API-only backend systems common in modern DevOps workflows

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πŸ”’ Security & Compliance Comparison

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Security FeatureFusion Agentic ApplicationsAdept
SOC2β€”β€”
GDPRβ€”βœ… Yes
HIPAAβ€”β€”
SSOβ€”β€”
Self-Hostedβ€”βŒ No
On-Premβ€”βŒ No
RBACβ€”βœ… Yes
Audit Logβ€”βœ… Yes
Open Sourceβ€”βŒ No
API Key Authβ€”βœ… Yes
Encryption at Restβ€”βœ… Yes
Encryption in Transitβ€”βœ… Yes
Data Residencyβ€”Configurable
Data Retentionβ€”Configurable
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