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Case Studies

Evidence Before Claims

Client engagements and internal reference builds, with named technologies and engineering decisions. Start with your constraint: reliability, cost, governance, latency, or delivery risk.

Buyer Situation

Build Agent Systems For Live Use

Proof for teams shipping agents, HITL workflows, RAG systems, operational intelligence infrastructure, and automation into environments with real users and real failure cost.

Voice AgentsMeeting UX
Voice AI AI Agents Meeting Agents

Building a Governed Voice Agent for Real Business Meetings

ActiveWizards (Internal)

How ActiveWizards built Vox, an internal voice-agent reference platform focused on meeting presence, silence policy, approved context, interruption handling, and reviewable artifacts.

agent_posture: Silent by default
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AgentsAutonomous Workflow
Google Ads API Multi-Agent Systems Edge Computing

Autonomous PPC Engine with 72-Hour Signal Lead Time

ActiveWizards (Internal)

Real-time signal intelligence from GitHub Issues and StackOverflow, dual-angle creative, and edge-deployed landing pages at 15ms TTFB.

signal_lead_time: 72h
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Multi-AgentOps
CrewAI Claude Pydantic

Competitor Intelligence Agent: Structured Research Workflow

ActiveWizards (Internal)

Multi-agent system for repeatable competitive analysis across pricing, features, and positioning with structured Pydantic-validated output.

competitor_dimensions: 3
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RAGDeveloper Tools
RAG FAISS LangChain

Codebase Analysis Agent: 30 Seconds to First Answer

ActiveWizards (Internal)

Language-aware chunking with Tree-sitter, FAISS vector retrieval, and LLM reasoning. 30 seconds from upload to first contextual answer on any codebase.

time_to_first_answer: 30s
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Security ResearchAnalyst Workflow
Python AI Agents Public-Source Research

Aporia: Governed Threat Intelligence Research Assistant

ActiveWizards (Internal)

We built an analyst-supervised research assistant that organizes public-source security context into structured, reviewable reports for defensive research workflows.

architecture: Agent-Assisted
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HITLContent Engine
LangGraph CrewAI Pydantic

Pagezilla: Governed Technical Content Pipeline

ActiveWizards (Internal)

Multi-model LLM pipeline with Pydantic validators, generated D2 diagrams, and HITL review for reviewable technical publishing.

pydantic_validators: 12
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Operational IntelligencePublishing Infrastructure
Kit Cloudflare Pages RSS

Signals: Multi-Channel Intelligence Pipeline

ActiveWizards (Internal)

Server-orchestrated intelligence pipeline that turns source monitoring into email briefings, a searchable web archive, RSS surfaces, and platform-specific discussion posts.

delivery_surface: Email, web archive, RSS, social
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Buyer Situation

Scale Data & AI Platforms

Proof for buyers evaluating real-time data infrastructure, computer vision systems, and production AI platforms with downstream operating dependencies.

Next step

Let's architect your next system

Tell us about your system, the decision ahead, and the constraints. We will review the context and recommend the next step.

What happens next

  1. 1. Context We review the situation and constraints.
  2. 2. Fit We recommend an appropriate next step.
  3. 3. Scope If relevant, we discuss scope.

Direct contact with a principal engineer.

From the team behind Production-Ready AI Agents (Amazon, 2025)