Running Coral Bricks as a service, AI Infrastructure

Coral Bricks Agency Implementation, Building Profitable Agent Delivery

Learn how to architect and resell Coral Bricks inference capacity to clients building coding and research agents. This course covers API integration, cost modeling with cached reads, agent framework setup, and pricing strategies for recurring agent workloads.

Open the decision record for Coral Bricks

What does running Coral Bricks for clients commit 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
16 hours

Is Coral Bricks worth running as a client service?

The evidence supports Coral Bricks as an OpenAI-compatible, high-throughput inference endpoint with free cached reads that drops into named agent tools, which is enough to build a managed-service offer for coding and research agents. What remains unknown is any vendor plan price, client price, labor cost, overhead, or expected volume, so no investment or ROI figure can be stated.

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

  • Coral Bricks API key (cb_... created from the API keys page)
  • OpenAI-compatible requests to https://inference.coralbricks.ai/v1
  • At least one served model slug such as coralbricks/glm-5.3-fp4 or coralbricks/deepseek-v4.1-flash-fast-fp4
  • At least one client-side agent tool from OpenCode, Codex CLI, GitHub Copilot, Cursor, Cline, Continue, or aider
  • Client workload parameters: input tokens, cached input percentage, output tokens

People and inputs

  • Documentation review of OpenAI wire-format streaming tool calls and 1M-token long-context handling
  • Benchmark harness for decode throughput and cache hit rate against the published 340 tok/s P50 and 98.53% cache hit rate figures
  • Capacity planning notes for deciding between serverless and dedicated VPC with committed throughput and private KV storage
  • Cost-estimation worksheet built from the published $303 to $54 observed monthly cost comparison

Estimated investment: Vendor pricing is usage-based; the L1 data publishes no lowest plan price, no setup fee, and no committed-throughput rate. Use "Custom pricing, contact vendor" and require the agency to supply client price, labor, usage, and overhead before any investment figure is modeled.

Lessons in this course

7 lessons on running Coral Bricks for clients.

  1. 01Why Coral Bricks Changes Agency Inference Margins Before Your Next Retainer RenewalStrategy
  2. 02Coral Bricks Cache EconomicsConcept
  3. 03When to Adopt Coral Bricks: Your Client Runs Their Own Agent LoopEvaluation Rule
  4. 04Coral Bricks: Buy vs Skip (Agent Product Builders)Decision Framework
  5. 05The Coral Bricks Cache Blind Spot: Why Agencies Fail With Coral Bricks on Agent RetainersFailure Pattern
  6. 06Coral Bricks Client Agent Deployment (5-7 days)Implementation Blueprint
  7. 07Coral Bricks Client Agent Endpoint Handoff (Onboarding)Operating Procedure

Included with the course

7 working documents for delivering this service.

  • Coral Bricks Cost Model Worksheetworksheet
  • Agent Workload Scoping Checklistchecklist
  • OpenAI-Compatible API Integration SOPsop
  • Client Onboarding Template for Coding Agentstemplate
  • Cache Strategy Guide for Multi-Turn Researchguide
  • Pricing Tier Recommendation Matrixworksheet
  • IDE Integration Enablement Checklistchecklist

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