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AI Automation

Most "AI automation" is 70% ordinary code and 30% LLM — that is the mix that is reliable and cheap to run. We replace repeated human judgment with a system that calls a model only where reasoning is genuinely required, and skips it everywhere else. Everything ships to production with cost tracking and a kill switch, not as a demo.

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What "AI automation" actually means in 2026

The phrase gets used to describe everything from spreadsheet macros to fully autonomous agent flows. We use it specifically: replacing repeated human judgment with a deterministic system that calls an LLM where reasoning is genuinely required, and skips the LLM call where it is not. Most of what we ship is 70% traditional code, 30% AI — because that is the combination that is reliable, cheap to run, and easy to debug at 3am when something goes wrong. We are skeptical of "agentic" architectures for most ops work; tight integrations beat autonomy when the task has a clear definition of done.

What we build

Document processing pipelines that read invoices, contracts, or compliance forms and write structured data to your existing system of record. Customer-facing chatbots that actually route to a human when they should, with full conversation logging. Internal AI assistants that sit in Slack and answer questions against your private knowledge base, with citations. Categorization and tagging at scale — bank transactions, support tickets, product content. Content generation pipelines with human-in-the-loop approval gates. None of it is a demo. All of it ships to production with cost tracking and a kill switch.

Cost discipline

LLM bills can grow faster than your savings on labor. We bake cost tracking into every workflow from day one: per-task, per-user, per-feature. We use prompt caching aggressively where it applies — Anthropic Claude prompt-cache has a 5-minute TTL, so we structure system prompts to maximize hit rate. We choose smaller models where they meet the quality bar and reserve larger models for the cases that actually need them. Every flow we ship has an admin dashboard showing the last 30 days of spend by cost center, so you can see ROI without guessing.

Models, vendors, and where we actually land

We work with Anthropic Claude, OpenAI GPT, and Google Gemini. Where you land depends on your data sensitivity, your latency budget, and your existing relationships. Claude usually wins for code-adjacent work and long-context tasks; GPT-4o for vision and tool use; Gemini for cost-per-token on bulk classification. We are vendor-agnostic and document why we chose what for your specific workflow. If you have an enterprise agreement with a specific provider, we honor it and architect around it.

01What's included

Everything you need, nothing you don't.

Comprehensive deliverables designed for shipping, not for sandbagging.

AI Automation capability surface — visual summary of deliverables
[FIG. 01]Capability surface
  • 01

    Process analysis and automation opportunity identification

  • 02

    Custom AI model development and training

  • 03

    Workflow automation and orchestration

  • 04

    Chatbot and virtual assistant development

  • 05

    Data analysis and predictive modeling

  • 06

    AI-powered content generation and optimization

  • 07

    Integration with existing business systems

  • 08

    Training and ongoing support

02Specializations

Focused expertise in key areas.

  • 01

    Business process automation

  • 02

    Customer service chatbots

  • 03

    Content generation and optimization

  • 04

    Document processing and data extraction

03Track record

Numbers that speak for themselves.

150+
Automation Completed
98%
Client Satisfaction
5+
Years Experience
04Stack

Technologies we ship with.

A working toolkit, not a buzzword list. Every tool below is in active rotation.

  • Python
  • TensorFlow
  • OpenAI API
  • Zapier
  • Make.com
  • n8n
  • Machine Learning
  • Natural Language Processing
05Process

A systematic approach that ships exceptional work.

  1. 01
    Discovery & Planning

    Business process audit and AI opportunity assessment.

  2. 02
    Design & Prototyping

    Solution design and proof-of-concept development.

  3. 03
    Development

    AI model training and optimization.

  4. 04
    Integration & Implementation

    System integration and workflow implementation

  5. 05
    Testing, Deployment & Support

    Testing, validation, performance tuning and team training.

  6. 06
    Maintenance & Support

    Ongoing maintenance and support

06Investment

Transparent pricing, no surprises.

Every engagement is scoped as a fixed-price Sprint. You get the exact number on a free 30-minute discovery call — no hourly billing, no surprises.

Get a custom quoteTalk to us first
07FAQ

Questions, answered straight.

What kinds of business processes do you automate?
Lead enrichment, document classification, internal-tool ETL, support-ticket triage, and review/QA workflows are the most common. If a process has clear inputs, clear outputs, and somebody copying data between two systems, it is a candidate.
Do you build with LLMs or with deterministic workflow tools?
Both, depending on the task. Deterministic workflows (Make.com, n8n, custom Node) for steps that must not vary; LLMs for steps where understanding human text is the whole point. We default to the cheaper, simpler option and only add an LLM where it earns its keep.
How fast can you start?
Most engagements start within 1-2 weeks of the discovery call. If you need to start sooner, tell us on the call — we keep a small amount of capacity reserved for urgent work and will be honest about whether we can meet your date.
Do you work with companies outside Canada?
Yes. Creative Brain Inc. is based in Brampton, Ontario but works across North America, the EU, and AU. We bill in CAD, run async across time zones, and overlap a few hours daily with your team for live work.

Also consider

Agentic Workflow Sprint

Want autonomous AI agents running your ops work end-to-end (not just point automations)? The Agentic Workflow Sprint replaces manual processes with multi-step agent orchestration on n8n, Make, or custom code in 14 days.

See Agentic Workflow Sprint
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