OVERVIEW

Verdaca docs

This documentation covers Verdaca's deliberation platform — how it is architected, how to run your first session, and how to extend it with custom agents and adapter substrates. It is written for practitioners: consultants, engineers, and technical leads who need to understand the system well enough to configure and deploy it.

ADVISORY

Start with the Conceptual model before touching configuration — the two-axis pluggability diagram is the key to understanding every other section.

What's in these docs

Quick start

Three lines to run a deliberation session. Install the package, initialize a Studio, and pass a workflow name.

# Install Verdaca
pip install verdaca

# Initialise a session
from verdaca import Studio
session = Studio.create()
result  = session.run("[workflow-placeholder]")

Architecture at a glance

Verdaca is organized on two independent axes: swap the agent personas horizontally, swap the substrate adapters vertically. Neither axis requires changing the other.

Every request reaches the kernel through one channel-neutral gateway, after an auth-first spine of four checks — signature, identity, replay, and budget. See the front door in the conceptual model.

Verdaca two-axis pluggability architecture Plug-in personas — UX Expert, Data Scientist, Legal Counsel, Security Architect — connect into the Verdaca Kernel. The kernel connects to substrate-neutral adapter groups: Memory (Mem0, Letta), LLM Provider (Anthropic, OpenAI), and Compaction and Output (Forge, Caveman). HORIZONTAL AXIS — PLUG-IN PERSONAS UX Expert Data Scientist Legal Counsel Security Architect VERDACA KERNEL Deliberation loop · synthesis · audit trail VERTICAL AXIS — SUBSTRATE-NEUTRAL ADAPTERS MEMORY LLM PROVIDER COMPACTION & OUTPUT Mem0 Letta Anthropic OpenAI Forge Caveman