AI automation services for growing businesses.
Custom AI systems built inside the tools your team already uses. We are Toronto-based and work with profitable businesses across Canada and the United States. Audit to handoff in 2 to 6 weeks. Full ownership, no lock-in.
What Aurora does, at a glance.
- We build custom AI automation for profitable businesses with 5 to 50 people in Canada and the United States.
- Every engagement starts with a $2,000 audit so you know exactly what to build and when it pays back.
- Custom builds run $5,000 to $25,000 CAD. The full AI-OS platform runs $7,000 to $25,000 CAD.
- You leave with working systems inside your existing tools, full documentation, and complete infrastructure ownership.
- We offer ongoing maintenance on retainer or on-demand. No long-term contracts.
Updated May 2026
What AI automation services does Aurora Designs offer?
Aurora Designs offers five AI automation services: an AI audit to identify the highest-value opportunities, tool selection and setup to build on the right stack, custom automation builds to replace manual work, the Aurora AI-OS for a full platform approach, and maintenance to keep systems running as AI technology evolves.
Original framework
The Aurora Engagement Ladder
Five rungs that map to Aurora's services and the buyer journey. Most clients start at Diagnose and move up.
- 1Diagnose AI Audit. Map the workflows, find the spend, prioritize what to build first.
- 2Setup Tool Selection and Setup. Pick the right stack and configure it for your business.
- 3Build Custom Automation. Replace the manual work with systems that run inside your existing tools.
- 4Operate Aurora AI-OS. Run the business on a platform with agents, audit logs, and an operator dashboard.
- 5Sustain Maintenance and Support. Keep systems running as models, APIs, and business requirements change.
What is the Aurora AI-OS?
The Aurora AI-OS is a productized three-tier AI operating system: an agent layer that reasons and acts on your workflows, a structured database that logs every action for auditability, and an operator dashboard that gives your team visibility and approval gates over what the AI does.
Most AI tools feel unreliable in production because there is no way to see what they did, why they did it, or catch a mistake before it propagates. The Aurora AI-OS solves that. Every agent action is written to a structured audit log. Your operators see a live dashboard. Anything requiring human judgment goes to an approval queue before it executes.
This is not a chatbot. It is a platform. Aurora builds it inside your existing infrastructure, hands off full ownership at the end, and leaves your team with the documentation to run and extend it without us.
- Agent layer with your custom workflow automation and business logic
- Structured audit log, every agent action recorded with timestamp, input, and output
- Operator dashboard with live status, approval queues, and override controls
- Approval-gate UX for human review on high-stakes actions
- Full documentation, team training, and infrastructure handoff at completion
- No vendor lock-in, no ongoing license fees, no dependencies on Aurora
Read the complete architecture guide: Aurora AI-OS: Architecture, Safety, and Deployment
What is an AI audit and what does it include?
An AI audit is a two-week engagement where Aurora maps your actual workflows, quantifies the manual work costing you the most time and money, and delivers a prioritized build plan with ROI estimates for every opportunity. You leave knowing where to start, how much it costs, and when it pays back.
Most clients reach Aurora's other services after the audit. The audit is the answer to "where do we start and how do we know the investment is worth it?"
- Operations diagnostic across your team's real workflows, not hypotheticals
- Prioritized list of automation opportunities ranked by payback period
- ROI estimate for each opportunity in your currency (CAD or USD)
- Tool recommendation included: which platforms and integrations fit your business
- Clear build proposal with scope, pricing, and timelines for top opportunities
- Live 60-minute presentation of the findings with your leadership team
- Full documentation you keep, whether or not you build with Aurora
What does a custom AI automation build cost and include?
A custom AI automation build is an end-to-end system designed around your specific workflow, built inside the tools your team already uses, tested against your real data, and handed off with full documentation and training. Most builds return five or more hours per employee per week and pay back inside the first quarter.
Most clients reach this stage after an AI Audit. The scope and price are fixed before work begins.
AI lead qualification and routing
Inbound leads scored, prioritized, and routed automatically. Auto-reply drafts generated in your brand voice. Your sales team stops spending Monday mornings triaging and starts spending them selling. Typical outcome: first-response time down from hours to minutes, sales capacity up 30 to 60%.
AI-powered proposal and document generation
Proposals, statements of work, itineraries, and reports that used to take half a day now generate from a simple intake form. Your team reviews and sends instead of building from scratch. Typical outcome: a four-hour task becomes a two-minute review.
AI content engines
Blog posts, social content, email drafts, and campaign assets produced in your brand voice. Your marketing team becomes an editor instead of a writer. Typical outcome: content output multiplied by three to five, with quality held constant or improved.
AI agents for operations, sales, and support
Autonomous or semi-autonomous AI agents that handle meeting prep, pipeline hygiene, customer onboarding, research, reporting, and handoffs between systems. Typical outcome: five or more hours returned per employee per week, with fewer dropped tasks and cleaner data.
How does Aurora help select and set up AI tools?
Tool recommendation is included inside the $2,000 AI Audit: you leave knowing which platforms fit your business, your team, and your existing stack. Hands-on setup, configuration, and team onboarding are scoped and quoted separately after the audit when needed.
Recommendation (included in AI Audit)
You leave the audit with a specific vendor shortlist and recommendation memo. Which automation platform fits your workflow (for example, n8n vs Zapier). Which AI model fits your use case and budget. Which CRM or data tools integrate cleanly with what you already have. The recommendation is opinionated, not a list of options.
Setup (scoped after Audit)
When hands-on installation is needed, Aurora quotes a setup engagement after the audit. This covers vendor account setup, baseline configuration, API integration with your existing stack, and a team onboarding session so your people know how to use what was built. Scoped per project, fixed price, no surprises.
What does ongoing maintenance and support look like?
Aurora offers ongoing maintenance for AI systems it has built. This includes monitoring, prompt and model tuning as upstream LLMs change, integration patches when third-party APIs shift, and light feature additions. Available on-demand or as a monthly retainer. No long-term contracts, no lock-in.
On-demand
Send a request, get a scoped quote within one business day. Work billed per change. Best for clients who need occasional help but do not anticipate regular support needs. Small changes are typically quoted in hours, not days.
Monthly retainer
A fixed block of hours per month, typically five to twenty, for clients who want a standing relationship. Covers model and prompt updates when providers ship breaking changes, integration patches, documentation updates, small feature additions, and team re-training when staff turns over. Month-to-month, no minimum term.
What maintenance covers: bug fixes, model and prompt updates, API integration patches, light feature additions, documentation updates, team re-training.
What maintenance does not cover: new automations from scratch, new AI agents, anything requiring a fresh scoping exercise. Those are Custom Builds.
How does a typical Aurora engagement run?
A typical Aurora engagement runs in five steps: a free 30-minute intro call to establish fit, a two-week AI audit to find the opportunity, a scoped-and-fixed quote, a two-to-six week build tested against your real data, and a full handoff that transfers documentation, credentials, and infrastructure to your team.
- Free intro call (30 minutes). We ask about your workflows. We tell you honestly whether we can help. If we cannot, we will usually tell you who can.
- AI audit (2 weeks). We map workflows, quantify the cost of the manual work, and deliver a prioritized build plan with ROI estimates. You own the deliverable regardless of next steps.
- Scope and quote. Fixed price, clear deliverables, firm timeline. No change-order games. You know the number before work begins.
- Build and test (2 to 6 weeks). We build inside your environment, test with your real data, and iterate until it works the way your team needs it to work.
- Handoff. Full documentation, team training, and infrastructure ownership transferred to you. We are a call away if you need us, but you will not need us to keep it running.
Who does Aurora work with (and who is it not for)?
Aurora works with profitable businesses in Canada and the United States, typically five to fifty people, where there is real operational pain and a team big enough to benefit from automation. Clients are honest about their constraints, timelines, and what their team will actually adopt.
Who it is for
- Profitable businesses with 5 to 50 people
- Professional services firms, B2B sales teams, finance and fintech operators, marketing and media businesses
- Founders or operators who are honest about constraints, the timeline, and what their team will actually adopt
- Clients ready to make a decision in the next 30 to 60 days
Who it is not for
- Pre-revenue or early-stage startups without proven workflows to automate
- Businesses looking for a chatbot to drop into a website and forget about
- Teams that want to be told what is possible rather than what is worth doing
Why work with Aurora instead of building it in-house?
Aurora builds inside your existing tools rather than requiring your team to learn new platforms, pressure-tests every project against a simple ROI question before scoping it, and transfers full infrastructure ownership at handoff. No lock-in, no ongoing licenses, no black boxes.
Built around your existing tools, not ours.
The fastest way to make an AI project fail is to force your team to learn a new platform. Aurora builds inside your existing stack, your existing CRM, your existing inbox, your existing project tool. Your team keeps working the way they already do. They just stop doing the manual parts.
Every project has to earn its place.
Before scoping anything, Aurora pressure-tests it against a simple question: is the payoff big enough, likely enough, and fast enough to justify the effort it will take your team to adopt it? If the answer is no, we say so. We would rather lose a deal than oversell a timeline.
You own everything.
When Aurora hands off, you own the infrastructure, the documentation, the credentials, and the IP. No vendor lock-in. No ongoing license fees that balloon at renewal. No black boxes. We run Aurora itself on this platform: our own content production, LinkedIn cadence, and client operations all run through our AI-OS.
We qualify hard before we quote.
Aurora asks hard questions on the intro call. We walk away from engagements we do not think we can win. We scope honestly so the outcome is inevitable, not hopeful. Owners of profitable businesses do not buy features. They buy an answer to "will this actually work in my business?"
How does Aurora compare to other AI consultancies?
Aurora's four closest alternatives are hiring an in-house AI engineer, subscribing to generic AI tools, engaging an enterprise consultancy, or working with a hobbyist AI agency. Each involves a different tradeoff on cost, speed, customization, and ongoing dependency.
Choosing an AI automation partner? Read: How to Choose an AI Automation Agency (2026 Guide)
Aurora Designs vs hiring an in-house AI engineer
| Factor | Aurora Designs | In-house hire |
|---|---|---|
| Cost | $5,000 to $25,000 one-time | $120,000 to $180,000 per year, fully loaded |
| Ramp time | 2 to 6 weeks to production | 3 to 6 months minimum |
| Scope flexibility | Project-specific, scoped before start | Broad but unfocused without direction |
| Ownership | Full infrastructure transfer at handoff | Knowledge lives with the employee |
| Risk | Fixed price, defined deliverable | Hiring risk, ramp risk, retention risk |
Aurora Designs vs generic AI tools (ChatGPT, Copilot, Zapier AI)
| Factor | Aurora Designs | Generic AI tools |
|---|---|---|
| Customization | Built for your specific workflow | One-size-fits-all, generic prompts |
| Adoption | Works inside your existing tools | Requires team behavior change |
| Maintenance | Documented, you own it | Dependent on vendor roadmap and pricing |
| Stickiness | Designed to match actual workflow | Most are abandoned within months |
| Support | Available on-demand or retainer | Help docs and community forums |
Aurora Designs vs enterprise consultancies (Deloitte, Accenture)
| Factor | Aurora Designs | Enterprise consultancy |
|---|---|---|
| Timeline | 2 to 6 weeks to production | 12 to 18 months for transformation projects |
| Price | $5,000 to $25,000 CAD | $100,000 to $500,000 or more |
| Scope | Targeted, high-ROI, measurable | Broad transformation, hard to attribute |
| Payback | Inside first quarter in most cases | Two to three years typical |
| Right for | Growing businesses with 5 to 50 people | Enterprise organizations with 500+ people |
Aurora Designs vs hobbyist AI agencies
| Factor | Aurora Designs | Hobbyist AI agency |
|---|---|---|
| Production readiness | Tested against real data, real edge cases | Demo-quality, often not stress-tested |
| Documentation | Full handoff docs, your team can modify | Minimal or none |
| Ownership | 100% yours, full infrastructure transfer | Often platform-locked or agency-controlled |
| Post-handoff | Available on-demand or retainer | Often difficult to reach after delivery |
| Tech stack transparency | You know exactly what was built and why | Black box, hard to audit or extend |
What results have Aurora clients seen?
Aurora clients across B2B SaaS, specialty finance, and commercial lending have eliminated hours of manual work per deal, multiplied content output, and significantly reduced lead response times. Every result below is from a production system, not a prototype.
"The automation and workflow systems they implemented significantly streamlined our internal processes, allowing my team to focus more on high-value opportunities and less on manual tasks. The efficiency gains were immediate, and the structure they have built is robust and scalable."
"Aurora built us a lead scoring and routing system that transformed how we handle inbound. Response times dropped by 30 to 50%, and we stopped losing deals to our own inbox."
Deal intake processing went from 45 minutes per deal to under 2 minutes. The system runs automatically on every new submission and has not required manual intervention since launch.
What does AI automation cost in 2026?
AI automation for growing businesses ranges from $2,000 CAD for a diagnostic audit to $5,000 to $25,000 CAD for a production build or full AI-OS platform. According to McKinsey's 2024 State of AI report, 72% of organizations now use AI in at least one business function, and implementation costs have dropped substantially over the prior two years. Payback periods for targeted automation typically fall between 3 and 9 months.
| Service | Price (CAD) | Timeline | What you get |
|---|---|---|---|
| AI Audit | $2,000 | 2 weeks | Workflow diagnostic, opportunity map, ROI-ranked build plan, tool recommendation |
| Tool Selection and Setup | Recommendation bundled in Audit; Setup scoped after | Varies | Vendor setup, configuration, team onboarding for chosen stack |
| Custom Automation Build | $5,000 to $25,000 | 2 to 6 weeks | Working system, full documentation, ownership transfer, team training |
| Aurora AI-OS | $7,000 to $25,000 | 4 to 10 weeks | 3-tier platform, audit log, operator dashboard, full ownership |
| Maintenance and Support | Scoped on request | Month-to-month or on-demand | Monitoring, patches, model updates, light feature work |
Want to model the ROI before committing? Read: How to Calculate ROI on AI Automation Before You Spend a Dollar or use the interactive calculator.
Frequently asked questions
How much does AI automation cost for a small business in Canada or the US?
For most businesses, meaningful AI automation starts with a $2,000 CAD audit. Custom builds typically run $5,000 to $25,000 CAD. The Aurora AI-OS, which adds a database layer and operator dashboard, runs $7,000 to $25,000 CAD. Payback periods typically fall between three and nine months, depending on how much manual work the system eliminates.
How long does it take to implement AI automation?
Aurora Designs audits take two weeks. Most custom automation builds ship in two to six weeks from kickoff. The Aurora AI-OS, a full three-tier platform, takes four to ten weeks. A firm timeline is provided before anything starts.
Do you work with US-based businesses?
Yes. Roughly a third of Aurora Designs' clients are based in the United States. The AI automation work is the same. Canadian clients also benefit from jurisdiction-specific guidance on PIPEDA and Quebec's Law 25, but the core engineering is identical.
What tools does Aurora build with?
Aurora builds inside whatever stack you already use. Common integrations include HubSpot, Salesforce, Pipedrive, Airtable, Notion, Slack, Microsoft 365, Google Workspace, and Webflow. AI platforms include Claude, OpenAI, n8n, Zapier, and LangChain. The tool chosen is always the one that fits your business, not the one Aurora prefers.
What happens if we want to change something after the handoff?
Everything Aurora builds is documented for your team to modify. Most clients make changes themselves. If you want Aurora to do it, small changes are quoted in hours, not days. Aurora also offers optional maintenance retainers for clients who prefer a standing relationship.
Do you offer ongoing maintenance and support?
Yes. Aurora offers on-demand support (scoped per change) and monthly retainers for clients who want a standing relationship, typically five to twenty hours per month. There are no long-term contracts and no lock-in. Most clients run their systems day-to-day without support.
What if the audit shows AI is not the right answer?
If the real bottleneck is a process issue, a tool issue, or a headcount issue rather than an automation opportunity, Aurora will say so. The audit deliverable is yours to keep either way. Aurora would rather lose a deal than oversell a timeline.
How is this different from the AI tools we already tried?
Generic AI tools force your team to change how they work. Aurora builds systems around how your team already works, inside your existing tools and workflows. That is why Aurora systems tend to stay in use a year later, instead of quietly dying in a forgotten browser tab.
What is the Aurora AI-OS and how is it different from a custom build?
A custom build delivers one or more automations inside your existing tools. The Aurora AI-OS adds two layers on top: a structured database that logs every agent action for auditability, and an operator dashboard where your team can review, approve, and monitor what the AI is doing. It is the difference between an automation and a platform.
Ready to see what this looks like for your business?
Book a free 30-minute intro call. We will ask about your workflows, tell you honestly whether there is a fit, and point you in the right direction whether or not we end up working together.