Running conw as a service, AI Chatbots

Conw Agency Implementation, Private AI Chatbots for Client Workflows

Learn how to deploy Conw's locally-hosted 12B model as a white-label chatbot service for clients. This course covers setting up private vocabulary memory, building the guarded learning loop with your team, integrating via OpenAI-compatible APIs into custom client tools, and packaging these capabilities into retainer-based offerings without external API dependencies.

Open the decision record for conw

What does running conw for clients commit you to?

Published figures for this service. Blank fields are not published.

Monthly tool cost
$0.50/month (lowest paid plan) or free tier with weekly token allowance
Time to first value
Not published
Payback
Not modeled (requires client pricing, labor costs, usage, and overhead).
Guided implementation
8 hours

Is conw worth running as a client service?

The evidence supports that Conw is a viable niche offering for privacy-focused clients needing a locally-served, learning chatbot. The low setup complexity and pay-as-you-go API enable quick prototyping, but the lack of explicit pricing and multi-client management features means agencies must validate their own delivery model and costs.

An agency-fit judgement for reselling this service. It is separate from the tool description on the decision record.

Before you start

What has to be in place before the first client engagement.

Tools and subscriptions

  • OpenAI SDK
  • Hugging Face
  • Conw account (free tier or paid)

People and inputs

  • Local machine or server with at least 16GB RAM (based on the stated hardware requirement)
  • Access to the open-source model (Conway-Retrain 12B or Conway-Omega 188M) via Hugging Face
  • Conw platform for managing learning and memory
  • API documentation for the OpenAI-compatible endpoints

Estimated investment: Lowest paid plan cost of $0.50/month (vendor cost) plus any hardware or hosting costs (not specified).

Included with the course

7 working documents for delivering this service.

  • Conw Deployment Checklist for Agency Teamschecklist
  • Private Vocabulary Training SOPsop
  • Client Onboarding Template for Local Model Setuptemplate
  • Learning Queue Audit Worksheetworksheet
  • OpenAI-Compatible API Integration Guideguide
  • Retainer Pricing Model for Conw Servicestemplate
  • Safety Filtering and Governance Playbookguide

Listed by name. These documents are not yet published as individual downloads.