Enterprise Agentic PDLC Platform

Blaze NexGen
Architecture

The industry's first governed Product Development Lifecycle platform. 78 specialized AI agents orchestrated across 4 phases with mandatory TDD (Test-Driven Development), BDD (Behavior-Driven Development), CDD (Compliance-Driven Development), and end-to-end test automation — delivering compliant, auditable software at enterprise scale.

78
AI Agents
4
AI Models
4
PDLC Phases
50+
Automation Scripts
12
Instruction Categories
>90%
Compliance Target
01 / 10

Platform Technology Stack

Six-layer architecture from AI models to infrastructure, each layer independently scalable and governable.

Layer 6 AI Models
Claude Sonnet Claude Opus Gemini Pro GPT-4o Model Router
Layer 5 Orchestration
SDLC Orchestrator PR Orchestrator CDD Methodology Pipeline Orchestrator Service Orchestrator
Layer 4 Governance
Quality Gates Trust Enforcer Compliance Manager Regulatory Analysis AI Governance Advisor
Layer 3 Enforcement
Compliance Monitor Evidence Generator Workflow Validator Industry Rule Engine Injection Scanner
Layer 2 Intelligence
50 Instructions 10 Rule Categories 27 Config Files Memory Bank Knowledge Graph
Layer 1 Infrastructure
AWS EKS Cloudflare Workers Cloudflare Pages Terraform IaC OTP Auth Layer

PDLC — Four-Phase Lifecycle

Every product change traverses four governed phases with mandatory quality gates and evidence collection.

Phase 01

Strategic Intelligence

  • Critical Thinking Analysis
  • PRD Generation with BDD Gherkin
  • Architecture Review
  • Risk Assessment
  • Regulatory Analysis
  • CDD Evidence: Phase 1
⛨ Gate: BDD scenarios in PRD
Phase 02

Automated Development

  • Git Worktree Isolation
  • TDD: Tests Before Code
  • Code Quality Review
  • Security Vulnerability Scan
  • E2E Playwright Testing
  • CDD Evidence: Phase 2
⛨ Gate: ≥80% coverage, all pass
Phase 03

Orchestrated Deployment

  • CI/CD Pipeline Execution
  • Trust Boundary Enforcement
  • Supply Chain Validation
  • Preview Environment Deploy
  • Health Check Verification
  • CDD Evidence: Phase 3
⛨ Gate: Pipeline green, trust verified
Phase 04

Lifecycle Management

  • 9-Agent PR Review Consensus
  • Multi-AI Model Validation
  • Compliance Score ≥90%
  • Context Capsule Generation
  • Final CDD Attestation
  • Human Approval Gate
⛨ Gate: ≥90% compliance, 0 critical

Three-Tier Agent Hierarchy

78 specialized agents organized into three tiers: Primary orchestrators, Visible specialists, and Hidden operators.

Tier 1 — Primary

2

Master orchestrators that coordinate the entire PDLC. Tab-switchable, always available.

sdlc-orchestrator review-orchestrator

Tier 2 — Visible

10

User-invokable specialists via @mention. Deep expertise in specific domains.

critical-thinking prd-generator codebase-mapper hypothesis-reasoning playwright-e2e evidence-collection test-coverage compliance-mgr jira-manager github-issues

Tier 3 — Hidden

66

Internal agents called only by orchestrators. Security, deployment, domain-specific, and utility operations.

security-reviewer architecture-reviewer code-quality trust-enforcer cloudflare-publisher pipeline-orchestrator banking-orchestrator aml-analyzer risk-calculator bpmn-specialist model-router + 55 more

Multi-AI Consensus Pipeline

Every PR artifact is validated through a 4-stage pipeline with discourse synthesis to eliminate single-model blind spots.

Stage 1

Fast Triage

Rapid bug detection, security basics, code style enforcement

Claude Sonnet
Stage 2

Deep Analysis

Architecture review, edge cases, subtle logic bugs, complex reasoning

Claude Opus
Stage 3

External Validation

Independent review from external providers running in parallel

Gemini Pro GPT-4o
Stage 4

Discourse Synthesis

Cross-model debate resolves contradictions, deduplicates, elevates consensus findings

Multi-Model Consensus

Three-Orchestrator Integration

Master SDLC orchestrator coordinates CDD evidence collection and PR review consensus across all four phases.

◎ SDLC Orchestrator
Master 4-Phase Workflow
Phase 1 Agents
Critical Thinking, PRD,
Architecture, Risk
Phase 2 Agents
Code Quality, Security,
Testing, E2E
Phase 3 Agents
Pipeline, Trust,
Supply Chain
Phase 4 Agents
9-Agent PR Review,
Compliance, Attestation
⛨ CDD Methodology
Evidence at Every Phase
◎ PR Orchestrator
9+ Review Agents
Context Capsule
Compliance Score
Final Attestation

Four Pillars of Enforcement

Every product change is governed by mandatory TDD, BDD, CDD, and E2E test automation — enforced at every phase, not just suggested.

🧪

TDD

Test-Driven Development. Tests written before implementation. Red-Green-Refactor enforced via git history.

  • Tests committed before code
  • Coverage: ≥80% on new code
  • All tests pass before Phase 3
  • Git history verified for order
📋

BDD

Behavior-Driven Development. Gherkin scenarios define acceptance criteria. Stakeholder-readable, machine-executable.

  • Given/When/Then in every PRD
  • Scenarios block Phase 1 → 2
  • 100% scenario coverage required
  • Edge cases and error paths
🛡️

CDD

Compliance-Driven Development. Evidence auto-collected at every phase. Audit-ready from day one.

  • Evidence at all 4 phases
  • Final attestation and score
  • Compliance: ≥90% to merge
  • Regulatory mapping built in
🎯

E2E Automation

End-to-End Test Automation. Playwright-powered browser testing validates every user-facing flow automatically.

  • Playwright MCP integration
  • BDD scenarios → E2E tests
  • Cross-browser validation
  • Visual regression detection

Platform Capabilities

Enterprise-grade capabilities spanning the full product development lifecycle.

🤖

Agentic Orchestration

78 specialized AI agents in a 3-tier hierarchy. Master orchestrators coordinate domain specialists automatically.

78 specialized agents
🔄

Multi-AI Consensus

4-model validation pipeline with discourse synthesis. No single-model blind spots. External provider independence.

4 AI models in consensus

Governed Lifecycle

Phase-gated enforcement with quality gates. No phase transition without meeting mandatory thresholds.

4 quality gates enforced
📊

Compliance Evidence

CDD methodology auto-collects evidence at every phase. Audit-ready artifacts generated, not assembled after the fact.

>90% compliance target
🏗️

Enterprise Infrastructure

AWS EKS with 100% spot instances, Cloudflare edge workers, Terraform IaC, OTP-based access control.

9 Cloudflare Workers
🏦

Industry Verticals

Domain-specific agents for banking, trading, AML, and regulatory compliance. Basel III, PCI-DSS, SOX, GDPR built in.

7 banking domain agents
🔒

Security-First

Prompt injection scanning, trust boundary enforcement, supply chain validation, 9 always-block vulnerability categories.

9 auto-block categories
🧠

Hypothesis-Driven ADRs

Architecture decisions require falsifiable hypotheses, evidence classification (L0/L1/L2), and bounded validity.

3 assurance levels
📐

Process Modeling

BPMN 2.0 and DMN 1.3 process modeling with validation, simulation, and Camunda 7/8 compatibility.

6 process agents

Competitive Advantage Matrix

How Blaze NexGen compares to the EY + 8090 partnership and standalone competitors.

Capability Blaze NexGen EY + 8090 8090 Standalone
Multi-AI Consensus Review
Cross-model validation with discourse synthesis
4-model pipeline Single model Single model
Compliance-Driven Development
Automated evidence collection throughout lifecycle
Native CDD engine Consulting overlay Not available
Agent Ecosystem
Specialized, governed AI agents
78 agents, 3 tiers ~20 modules 4 modules
Phase-Gated Quality Gates
Mandatory thresholds block phase transitions
4 enforced gates Manual checkpoints No gates
TDD + BDD + E2E Enforcement
Tests-first and behavior-driven, machine-verified
Mandatory, verified Recommended Not enforced
Industry Vertical Agents
Banking, AML, regulatory compliance built-in
7 banking agents EY advisory Generic only
Hypothesis-Driven ADRs
Falsifiable decisions with evidence chains
L0/L1/L2 + WLNK Not available Not available
Process Modeling (BPMN/DMN)
Visual process design with validation
6 process agents Consulting-led Not available
Infrastructure as Code
Self-hosted, sovereign deployment
EKS + Terraform + CF Cloud SaaS Cloud SaaS only
Pricing Model
Cost structure and accessibility
Platform license $200/seat + consulting $200/seat/month

Market Positioning

Why PDLC, not SDLC — and how Blaze occupies a market category competitors haven't defined yet.

🏭 They Build a Software Factory

8090 calls itself a "Software Factory" — optimized for code generation speed. EY adds consulting wrappers. Their value proposition: write code faster. The problem: enterprises don't fail because they write code slowly. They fail because ungoverned code reaches production.

🛡️ We Build a Governed Platform

Blaze NexGen is a Product Development Lifecycle Platform — governed end-to-end from strategic intelligence to compliance attestation. Code generation is one capability among 78 agents. The value proposition: every artifact is auditable, every decision is traceable, every phase is gated.

📊 PDLC > SDLC — Why the Shift

SDLC is a phase within the product lifecycle. PDLC encompasses requirements, compliance, governance, delivery, and lifecycle management. Enterprise buyers budget by product line, not codebase. PDLC speaks their language and positions Blaze as the platform of record.

🎯 Addressable Market

EY+8090 targets enterprises willing to pay $200/seat + Big 4 consulting rates. Blaze targets the same enterprises with a platform-native approach that eliminates the consulting dependency. The platform IS the governance — not a slide deck that recommends it.