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Pricing & Scoping Guide

AI Consulting Cost: How Engagements Are Scoped & Priced

Understanding what drives the cost of an AI project is the fastest way to avoid wasted spend. We break down the 5 structural factors that determine scope, infrastructure fees, and engineering investment.

A Familiar Problem

Why AI pricing quotes vary wildly across the industry

One agency quotes $10,000 while another quotes $150,000 for what seems like the same feature. The difference usually lies in whether they are building a fragile API wrapper or an enterprise-grade, guardrailed production system.

Hidden ongoing token and infrastructure bills

Agencies delivering software without calculating ongoing cloud and LLM API costs, resulting in surprise monthly operational expenses.

Underestimating data preparation effort

Assuming unstructured PDFs and legacy spreadsheets can be plugged directly into an LLM without dedicated ingestion and cleaning pipelines.

Paying for generalist strategy with no code

Spending enterprise consulting rates for theoretical slide decks that provide no working software or intellectual property.

Engagement Scope

The 5 structural drivers of AI development cost

Every credible AI project quote is shaped by these five technical and operational requirements.

✓Task Complexity: Simple classification vs. multi-step agent reasoning with dynamic tool calling
✓Data Hygiene & Pipeline: Pre-structured SQL data vs. unstructured multi-format document ingestion (RAG)
✓Integration Surface: Standalone internal dashboard vs. bidirectional CRM/ERP and WebRTC voice sync
✓Model Selection & Hosting: Public cloud enterprise API vs. private VPC hosting with zero-retention rules
✓Safety & Evaluation Layers: Deterministic validation, automated drift testing, and human escalation workflows
Measurable Shift

Low-Cost API Wrapper vs. Production AI System

Operational DimensionWithout Clear ArchitectureWith The Squirrel
Scoping transparencyOpaque hourly rates with open-ended development timelines and scope creep.Fixed-milestone scoping with clear acceptance criteria and weekly deliverables.
Operational costsUnmonitored token calls leading to ballooning monthly cloud charges.Model routing and caching architecture optimized for sustainable margins.
Handover & IPOngoing platform subscriptions where you rent access to your own tools.100% intellectual property transfer, code repository ownership, and cloud configs.
Methodology

How we quote and scope projects

We believe in transparent, fixed-scope proposals before any contract is signed.

01

Step 1

Discovery call (30 min)

We review the specific workflow, target users, and current tools you want to connect.

02

Step 2

Technical scoping assessment

Our engineers analyze data accessibility, model selection, and integration requirements.

03

Step 3

Fixed-milestone proposal

We deliver a detailed project specification with fixed milestone costs, timeline, and deliverables.

04

Step 4

Sprint delivery

Work begins with weekly demos, shared progress, and direct access to senior engineers.

Verified Proof Point

From a Single Landing Page to a Two-Year Partnership

Read Case Study →

A two-year technical partnership delivering two parallel engines: a suite of internal web applications and dashboards for operational clarity, and an AI-powered data scraping and outreach system to fuel B2B sales.

5+

Internal Tools Delivered

100%

Lead Sourcing Automated

Questions & Answers

Frequently Asked Questions

Because responsible AI pricing depends entirely on your specific data structure, integration points, and security requirements. A quote given without seeing your data is either an inaccurate guess or a generic wrapper. We provide custom, fixed-milestone quotes within 24 hours of our initial scoping call.

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