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AWS Agentic AI Competency Assessment

Document Version: 1.0 Assessment Date: December 17, 2025 Platform: Vellocity (Vell) Target Competency: AWS AI Competency - Agentic AI Applications Application Deadline: January 21, 2026 (FTR SaaS Compliance)

Executive Summary

This document assesses Vellocity's readiness against the AWS AI Competency Agentic AI Categories announced at AWS re:Invent 2025 (December 1, 2025). The assessment evaluates compliance with technical requirements, AWS service integration, and governance standards.

Overall Assessment: READY WITH REMEDIATIONS

Category Status Score
Agentic AI Technical Capabilities ✅ COMPLIANT 95%
AWS Service Integration ⚠ PARTIAL 76%
Responsible AI & Governance ✅ COMPLIANT 90%
Security & Reliability ✅ COMPLIANT 93%
Customer Case Studies ❌ GAP 0%
Partner Path Prerequisites ⚠ PENDING 50%

Recommended Category: Agentic AI Applications (Software Path)

AWS Agentic AI Competency Requirements

Based on the AWS announcement, partners must demonstrate:

  1. Autonomous AI Solutions - Can perceive, reason, and act independently
  2. AWS AI Service Integration - Bedrock AgentCore, Strands Agents, SageMaker AI
  3. Responsible AI Development - Governance, monitoring, safety controls
  4. Technical Validation - Rigorous audit of agentic capabilities
  5. Customer Case Studies - Successful customer implementations
  6. Security, Reliability, Operational Excellence - AWS Well-Architected standards
  7. Prior Validation - Must be validated/differentiated member of Services or Software Path

Category Alignment

Three Agentic AI Categories

Category Description Vellocity Fit
Agentic AI Applications End-to-end solutions for specific use cases ✅ PRIMARY FIT
Agentic AI Tools Developer tools for building agents ❌ Not applicable
Agentic AI Consulting Services Implementation services ❌ Not applicable

Rationale: Vellocity is an end-to-end GTM platform for AWS ISV partners with autonomous AI workflows, making Agentic AI Applications the correct category.

Detailed Technical Assessment

1. Agentic AI Capabilities (Score: 95%)

1.1 Autonomous Decision-Making ✅

Requirement Implementation Evidence
Natural language task interpretation Claude-powered WorkflowPlanner app/Extensions/ContentManager/System/Services/AgentCore/WorkflowPlanner.php
Multi-step execution planning AgentOrchestrator with dependency resolution app/Extensions/ContentManager/System/Services/AgentCore/AgentOrchestrator.php
Dynamic step sequencing JSON workflow generation with _dependency_N injection Workflow templates
Error recovery Retry logic (max 3 attempts, exponential backoff) AgentOrchestrator

1.2 Perception System ✅

Data Source Purpose AWS Service
Brand Voice Context Consistent messaging S3 + Aurora MySQL
Marketplace Listings Compliance validation DynamoDB + Catalog API
Partner Intelligence Co-sell matching AWS CleanRooms
Competitive Data Market positioning Bedrock Knowledge Base
Social Analytics Performance tracking External APIs (exempt)

1.3 Reasoning Engine ✅

  • Workflow Planning: Claude autonomously generates execution plans from natural language
  • Dependency Resolution: Automatic step sequencing with data flow
  • Token Optimization: Budget-aware execution
  • Fallback Strategies: Alternative paths on failure

1.4 Action System ✅

35+ Agentic Capabilities Implemented:

Category Capabilities Count
Content Generation GenerateText, GenerateImage, GenerateContentSeries 5
GTM Intelligence CoSellMatching, JointGTMPlanner, PartnerIntelligence 6
Marketplace MarketplaceAwareness, CompetitorAnalysis, Compliance 5
Data Access QueryKnowledgeBase, FetchExternalUrl, AnalyzeContent 8
Social/Publishing PublishToSocialMedia, LinkedInGraph, BrandMonitoring 4
Enterprise AWSCleanRooms, CPPOGenerator, AceOpportunitySync 7

2. AWS Service Integration (Score: 76%)

2.1 Current AWS AI/ML Services ✅

Service Implementation Status
AWS Bedrock Runtime Claude 3.5/4.5, Nova, Haiku models ✅ Active
AWS Bedrock Knowledge Base RAG for document retrieval ✅ Active
AWS Bedrock Guardrails Content filtering, PII detection ✅ Active
AWS Bedrock Embeddings Titan embeddings ✅ Active
Amazon Polly Text-to-speech 🕒 Planned
AWS Lambda Event-driven processing ✅ Active
AWS Step Functions Workflow orchestration ✅ Active

2.2 Bedrock AgentCore Integration ⚠ GAP

Current State: Custom AgentOrchestrator (not Bedrock Agents)

Bedrock AgentCore Feature Vellocity Implementation Gap
Agent Runtime Custom PHP orchestrator Consider migration
Action Groups CapabilityRegistry (35+ tools) Equivalent
Knowledge Bases Bedrock KB integrated ✅ Aligned
Guardrails Bedrock Guardrails integrated ✅ Aligned
Memory Custom session management Consider Bedrock Memory

Recommendation: Evaluate migrating orchestration to AWS Bedrock Agents for stronger AWS alignment. Current custom implementation is functionally equivalent but may require justification during technical validation.

2.3 Non-AWS AI Providers ❌ GAP

Current State: 10 non-AWS LLM providers active (user-selectable)

Provider Usage Migration Path Priority
OpenAI GPT-4o High Bedrock Claude 🔴 HIGH
Google Gemini Medium Bedrock Claude 🔴 HIGH
Anthropic Direct API Medium Bedrock Claude 🟠 MEDIUM
DeepSeek Low Bedrock Claude 🟡 LOW
X.AI (Grok) Low Bedrock Claude 🟡 LOW
Perplexity Low Bedrock + Search 🟡 LOW
ElevenLabs TTS High Amazon Polly 🔴 HIGH

Required Action: Implement "Bedrock-Only Mode" for AWS Marketplace listing to achieve 100% AWS AI/ML compliance.

3. Responsible AI & Governance (Score: 90%)

3.1 AWS Bedrock Guardrails ✅

Guardrail Feature Implementation Status
Content Filters Hate, violence, sexual, insults, misconduct ✅
Denied Topics Custom topic-based filtering ✅
Word Filters Profanity and custom lists ✅
Sensitive Info Filters PII detection (SSN, credit cards, emails) ✅
Contextual Grounding Hallucination prevention for RAG ✅
Trace Logging Detailed audit trails ✅

3.2 Governance Controls ✅

Control Implementation Evidence
Per-capability guardrails Different guardrails per agent capability CapabilityRegistry
Audit logging All executions tracked ext_content_manager_agent_executions table
Credit monitoring Token usage tracking AgentOrchestrator
Team isolation Multi-tenant workspace separation Team-based access

3.3 Model Safety ⚠

Requirement Status Notes
Prompt injection prevention ✅ Bedrock Guardrails
Output validation ✅ Content filters
Bias mitigation ⚠ Implicit via model selection
Human oversight ✅ Approval workflows available

4. Security & Reliability (Score: 93%)

4.1 AWS Security Services ✅

Service Purpose Status
AWS IAM Cross-account roles, least privilege ✅ Active
AWS Cognito Enterprise SSO, MFA ✅ Active
AWS KMS Encryption key management ✅ Active
AWS Secrets Manager API credentials ✅ Active
AWS WAF Web application firewall ✅ Active
AWS GuardDuty Threat detection ✅ Active
AWS Security Hub Centralized findings ✅ Active
AWS CloudTrail API audit logging ✅ Active

4.2 Security Hub Compliance Controls ✅

Recent security hardening (CloudFormation templates):

Control Implementation File
EC2.2 Default Security Group Lockdown Lambda-automated revocation cloudformation/account/baseline-security.yml
EC2.172 VPC Block Public Access Account-level IGW blocking cloudformation/hardening/network-hardening.yml
GuardDuty.11 Runtime Monitoring Enabled Baseline security stack

4.3 Data Protection ✅

Protection Implementation
At-rest encryption S3 (AES-256), RDS (KMS), EBS (KMS)
In-transit encryption TLS 1.2+ for ALB, RDS, Redis, APIs
Key rotation Automatic annual KMS rotation
Cross-account access External ID protection

5. Customer Case Studies (Score: 0%) ❌ CRITICAL GAP

Requirement: AWS requires documented customer implementations demonstrating successful agentic AI deployments.

Requirement Status Action Required
2+ Customer References ❌ Not documented Gather references from early adopters
Written Case Studies ❌ Not created Create 2-3 case studies
Measurable Outcomes ❌ Not documented Document ROI, time savings
Customer Testimonials ❌ Not collected Collect quotes

Recommended Case Study Structure: 1. Customer Overview - Company name, size, industry 2. Challenge - GTM pain points before Vellocity 3. Solution - Agentic capabilities deployed 4. Results - Quantified outcomes (time savings, pipeline impact) 5. AWS Services Used - Bedrock, CleanRooms, etc.

6. Partner Path Prerequisites (Score: 50%)

6.1 Software Path Requirements

Requirement Status Notes
AWS Partner Network membership ✅ Required for application
Software Path validated ⚠ Verify status in Partner Central
FTR (Foundational Technical Review) ❌ Deadline: January 21, 2026
AWS Marketplace listing ⚠ In progress

6.2 FTR Compliance Status

FTR Requirement Vellocity Status Gap
Core infrastructure AWS-native ✅ 93% None
AI/ML AWS-native ❌ 29% Need Bedrock-only mode
Data storage AWS-native ✅ 100% None
Compute AWS-native ✅ 100% None

Compliance Gap Summary

Critical Gaps (Must Fix Before Application)

Gap Priority Effort Timeline
Customer Case Studies 🔴 CRITICAL Medium 4-6 weeks
Bedrock-Only Mode 🔴 CRITICAL Low 1-2 weeks
FTR Review Completion 🔴 CRITICAL Medium 4-8 weeks
Gap Priority Effort Notes
Bedrock Agents migration 🟠 MEDIUM High Evaluate cost/benefit
Amazon Polly integration 🟠 MEDIUM Low Replace ElevenLabs
Strands Agents evaluation 🟡 LOW Medium New framework

Remediation Roadmap

Phase 1: Immediate (Before January 21, 2026)

  1. Implement Bedrock-Only Mode
  2. Create feature flag to disable non-AWS LLM providers
  3. Update default model settings to Bedrock Claude

  4. Document AWS-only configuration for FTR submission

  5. Gather Customer References

  6. Identify 3-5 early adopter customers
  7. Request permission for case study development

  8. Begin case study interviews

  9. Complete FTR Preparation

  10. Review docs/PLATFORM_CAPABILITIES_AWS_NATIVE_ASSESSMENT.md
  11. Document Bedrock-only architecture
  12. Prepare FTR submission materials

Phase 2: Short-term (Q1 2026)

  1. Develop Case Studies
  2. Write 2-3 detailed customer success stories
  3. Include quantified AWS service usage

  4. Get customer approval

  5. Migrate TTS to Amazon Polly

  6. Replace ElevenLabs with Polly neural voices

  7. Update voice synthesis workflows

  8. Submit AI Competency Application

  9. Navigate to Partner Central > AI Competency
  10. Use automated validation tool
  11. Submit with case studies

Phase 3: Medium-term (Q2 2026)

  1. Evaluate Bedrock Agents Migration
  2. Assess benefits of native Bedrock Agent runtime
  3. POC migration of AgentOrchestrator

  4. Decision: migrate vs. maintain custom

  5. Achieve 100% AWS AI/ML

  6. Remove non-AWS engine options entirely
  7. Update EngineEnum.php to Bedrock-only
  8. Pass full FTR compliance

Benefits of AWS AI Competency Achievement

Per the announcement, achieving Agentic AI Competency provides:

Benefit Value
Marketing Development Funds (MDF) $50K base + $25K agentic bonus = $75K
Business Outcomes Xcelerator Plus (BOX+) Priority access
Future GTM Pilots Priority access
AWS Partner Finder Featured listing
APN Blog / Social Promotion Launch partner visibility

Conclusion

Vellocity demonstrates strong alignment with the AWS Agentic AI Competency requirements:

  • Strengths: True agentic architecture (autonomous reasoning, 35+ capabilities), AWS-native infrastructure (93%), Bedrock integration (guardrails, knowledge bases), enterprise security
  • Critical Gaps: Customer case studies, Bedrock-only mode enforcement, FTR completion
  • Estimated Time to Compliance: 6-8 weeks with focused effort

Recommended Next Steps: 1. Immediately implement Bedrock-only mode feature flag 2. Begin customer case study development this week 3. Schedule FTR pre-review with AWS partner team 4. Target AI Competency application: February 2026

References

Document Version 1.0 - Created December 17, 2025 For AWS AI Competency application questions, contact your AWS Partner Development Manager