Running AgileSoftLabs as a service, AI Agents
AgileSoftLabs Agency Implementation, White-Label AI Agent Delivery
Learn how to scope, price, and deliver custom AI agents for your clients using AgileSoftLabs' LLM-assisted development platform. This course covers outcome-based pricing models, multi-model LLM selection for regulated industries, vector database configuration for RAG workflows, and 60-90 day project delivery cycles that compress timelines by 40-60% while maintaining full IP ownership for resale.
Open the decision record for AgileSoftLabsWhat it commits you to
Published figures for this service. Blank fields are not published.
- Monthly tool cost
- Not published
- Time to first value
- Not published
- Payback
- Not modeled
- Guided implementation
- 8 hours
Assessment
AgileSoftLabs offers credible AI engineering capabilities with outcome-based pricing, but agencies need technical depth and must gather pricing details directly.
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 API access
- Docker and Kubernetes for containerization
- Cloud platform account (AWS, Azure, or GCP)
- Vector database such as Pinecone or Weaviate
People and inputs
- Technical staff with AI/ML experience
- Project management for scope definition
- Legal review of outcome-based contracts
Included with the course
7 working documents for delivering this service.
- AI Agent Scope Definition Worksheetworksheet
- Outcome-Based Pricing Calculator for AI Modulestemplate
- LLM Model Selection Checklist (OpenAI, Claude, Gemini, LLaMA)checklist
- Vector Database Configuration SOP for RAG Implementationsop
- 60-90 Day AI Agent Delivery Roadmap Templatetemplate
- Client Infrastructure Assessment Guide (AWS, Azure, GCP)guide
- White-Label Resale Agreement and IP Ownership Checklistchecklist
Listed by name. These documents are not yet published as individual downloads.