Question 1

What does DevQueens do?

Accepted Answer

DevQueens ships three deliverables for the same company: process automation that drains manual hours, AI agents that transact against the customer's product, and AI marketing that puts the business inside ChatGPT, Claude, and Perplexity where buyers now search. Every build is tailored to the specific company.

Question 2

How much does DevQueens cost?

Accepted Answer

Public pricing. Paid proof of concept: $3,000 to $7,000 in 5 to 10 days. Production automation build: $5,000 to $20,000 in 4 to 6 weeks. Production AI agent connector: $10,000 to $25,000 in 3 to 5 weeks. AI marketing audit from $1,500 with optional $300 per month monitoring. Ops retainer $1,500 to $3,000 per month after production goes live.

Question 3

How fast can DevQueens ship an automation or AI agent?

Accepted Answer

A paid proof of concept ships in 5 to 10 days. A production automation ships in 4 to 6 weeks. A production AI agent connector ships in 3 to 5 weeks, including Meta WhatsApp Business platform review and Braintrust or Langfuse evals.

Question 4

Why does every DevQueens engagement start paid?

Accepted Answer

The price is the filter. A free proof of concept attracts window shoppers who cost time. A paid proof of concept in the $3,000 to $7,000 band filters for buyers who have real manual hours to automate or a real agent surface to build, and it lets the team watch the thing actually work against the customer's data before anyone commits to production.

Question 5

How does DevQueens price its work?

Accepted Answer

Public prices, fixed scope, fixed timeline. The anchor is what you capture, not what we clock. An automation that clears 800 invoices a month returns 40 approver hours a week. An AI agent that captures 50 bookings a week unlocks real revenue. A profile audit that makes your business legible to ChatGPT turns searches into clients.

Question 6

What is included in the DevQueens ops retainer?

Accepted Answer

The monthly retainer covers OAuth token rotation, API schema drift, model release regressions that break tuned prompts, platform policy changes, eval maintenance including the security evals, and monthly security reviews. No emergency statements of work and no scope creep bills.

Question 7

Does DevQueens offer custom solutions per company?

Accepted Answer

Every build is tailored to the specific company. The three lines, process automation, AI agent surface, and AI marketing, are not shelf products: they are the three deliverables DevQueens builds around what the company already does and already has.

Question 8

What makes DevQueens different from other AI agencies?

Accepted Answer

Most agencies do one of the three lines, automation, AI agents, or AI marketing, and the three never talk to each other. DevQueens delivers all three under one roof so the data model, schemas, catalog, pricing, and voice stay consistent across the automation that drains manual hours, the agent that transacts on the product, and the marketing that puts the business in front of the buyer.

Browsing Guide.

How AI automation returns 40 hours a week to finance ops

GEO Marketing: How to get your business found by ChatGPT and Claude

What is an AI agent (and what it isn't)

Prompt engineering for product teams, without the mystique

How to set cost caps on an AI agent before you ship

Evaluating LLM outputs: a practical harness for small teams

Building AI agents on WhatsApp Business: what Meta allows