Fractalic Studio helps founders and leadership teams design and implement practical AI systems: clear processes, clear metrics, measurable impact.
No decks. We talk through your situation, then decide if it makes sense to work together.
Teams are experimenting with random AI tools, but nothing is standardised or measured.
Vendors sell "AI solutions" that look impressive in demos and disappear in operations.
Leadership feels the pressure to "do something with AI" without a clear map, budget, or owner.
The result: noise, duplicated effort, no ownership, and no link to revenue, cost, or risk.
Fractalic Studio is a boutique advisory focused on one thing: making AI deployment legible and controllable for the people who actually own the business. No magic, no vendor lock-in, no buzzword decks.
We map where AI can actually move numbers in your business, given your model, team, and constraints.
We shape concrete workflows, roles, and guardrails where AI makes sense — and cut what doesn't.
We stay close while you run pilots, adjust the design, and turn experiments into operating routines.
For: Founders and executives who want a sober view of where AI is worth the effort in their current business.
For: Teams that have decided to move and need a concrete plan, not another inspirational talk.
For: Leaders who want an external partner to keep the plan honest and moving.
For: Founders and executives who want to upgrade their own leverage with AI before rolling it across the company.
Anonymized examples of how we approach AI projects. Names and specific metrics withheld for confidentiality.
SEO and GEO (Generative Engine Optimization) best practices exist in fragmented documentation, making it difficult for businesses to implement systematic optimization strategies. Teams need a guided, step-by-step approach that tracks progress and exports actionable plans.
Built a free, interactive wizard tool that transforms an 80/20 SEO playbook into a guided experience: 82 expert tasks across 9 sections, auto-save progress with LocalStorage, contextual help for every task, export to Markdown/PDF. Premium UX with glassmorphism design, WCAG 2.1 AA accessibility, and zero signup friction.
Production tool deployed on Cloudflare Pages. Demonstrates lead generation through value-first content: users complete tasks, save progress locally (privacy-first), and export customized SEO strategies. Tool drives awareness while providing genuine utility. Built with vanilla JavaScript for maximum performance.
A digital signage integrator needed to convert website visitors into qualified leads. Static landing pages weren't working—prospects wanted answers before talking to sales: "What will this cost?" "Will it work for my use case?" "What's the ROI?"
Built 6 specialized interactive tools: ROI calculator, TCO comparison (digital vs static), ADA compliance checker, menu board audit, friction scorecard, and drive-thru cost estimator. Each tool provides instant value while capturing lead data with built-in qualification signals.
Production suite deployed to client subdomain. Each tool generates leads with rich qualification data. Client owns the tools, the leads, and the analytics. Demonstrates principle: not every problem needs AI—sometimes the right answer is a well-designed tool that solves a specific business problem.
A growing business needed to maintain consistent social media presence across 5+ platforms without dedicated marketing staff. Content creation was ad-hoc, posting was manual, and there was no connection between content performance and business outcomes.
Designed an AI-powered content workflow: automated content generation based on business context, intelligent scheduling with optimal timing, multi-platform publishing from single source, approval gates for quality control.
Reduced content creation time by 70%. Established repeatable publishing cadence. Created clear ownership: business owner approves, system executes.
An online fashion retailer faced high return rates (>30%) because customers couldn't visualize how clothing would look on them. Previous "virtual fitting" solutions were gimmicks that didn't affect purchase behavior.
Built a practical virtual try-on system: realistic outfit visualization on user's body type, integration with existing product catalog, seamless checkout experience, explicit measurement tracking correlation between widget usage and return rates.
Widget deployed to production store. System designed with clear metrics: widget engagement → conversion rate → return rate impact. Ownership assigned to merchandising team.
An individual wanted to preserve and structure their digital knowledge — documents, notes, decisions, personal history — in a way that could be useful for themselves and potentially their family.
Designed a personal AI system: ingests and organizes disparate digital content, creates searchable AI-queryable knowledge base, maintains privacy with local-first architecture, simple enough to use daily.
Working prototype with local-first architecture. Clear scope: what stays private, what can be shared. User owns their data and the system that processes it.
A logistics company received hundreds of daily customer inquiries about shipment status, pricing, and delivery windows. Support staff spent 80% of time on repetitive queries, leaving complex issues unaddressed.
Designed a conversational AI layer: connected to real-time shipment tracking, handled standard queries without human intervention, escalated complex cases with full context, tracked deflection rate and satisfaction.
Reduced routine query load on support team. Established clear handoff protocol: AI handles what it can, humans handle what they should. Metrics defined: response time, deflection rate, escalation quality.
Presenters and educators needed better cursor visibility during screen sharing and recordings. Existing solutions were either too complex or didn't work reliably on macOS.
Built focused, single-purpose utilities: cursor spotlight for visibility during presentations, minimal system resource usage, native macOS integration. Philosophy: do one thing well, ship it, move on.
Published to App Store. Demonstrates approach: not every problem needs AI. Sometimes the right answer is a simple, well-designed tool.
A content team needed to produce short animated videos quickly without specialized animation skills or expensive production pipelines. Traditional workflows required multiple specialists and weeks of coordination.
Built an end-to-end automated pipeline: 53 lines of prompt → finished .mp4 lands on your desktop. AI-generated poetry/script, visual generation through specialized image models, automated video assembly. Multiple AI models orchestrated deterministically under Fractalic AI orchestration.
Production time reduced from weeks to minutes. One person with a prompt produces broadcast-ready content. Demonstrates principle: AI is most powerful when models are composed, not used in isolation.
A 3D printing company handled hundreds of small orders (<$1,000) manually. Each deal required: lead qualification, quote generation, task assignment to operators, customer follow-ups, and payment tracking. Staff spent 80% of time on process, not production.
Designed and deployed a HubSpot automation system that runs the entire pipeline autonomously: receives inbound leads, qualifies and routes automatically, assigns production tasks to operators, sends status updates at each stage, tracks to payment. Human intervention only for exceptions.
End-to-end automation from first contact to payment received. Operations team refocused on production quality instead of admin. Clear metrics: deals processed, time-to-close, human intervention rate. Bot manages flow, humans manage exceptions.
You share context and constraints. We ask direct questions. If there is no meaningful value to create, we say so.
Clear scope, timelines, fees, and decision points. No hidden upsell.
Short cycles, written artifacts, and explicit owners on your side.
We design ourselves out. The goal is not dependency; the goal is a system you own.
We work best with:
If you want inspirational keynotes or a chatbot on your homepage, we are not the right firm.
AI that connects to real business outcomes — revenue, cost, risk, time. Not demos, not experiments without owners, not technology for its own sake.
We don't sell transformation narratives. We map your existing structure, find where AI fits, and design systems with clear ownership. We build ourselves out, not in.
Primarily 5-150 people. Large enough to have real processes and constraints. Small enough that founders and leadership still own key decisions.
Both. We design the system (processes, roles, metrics) and can support implementation. But we always leave you with documentation and governance to run it without us.
AI Opportunity Audit: 2 weeks. Operating Blueprint: 4-6 weeks. Implementation Advisory: ongoing retainer with defined scope.
We focus on business structure, not industry. Our work spans e-commerce, logistics, professional services, and SaaS. The common thread: founders who want AI under control, not AI controlling them.
Yes, if you have real revenue and repeatable work. If you're pre-product or still searching for product-market fit, AI strategy is premature.
You own everything: the documentation, the decision logs, the governance framework. We design for exit, not dependency.
It depends on your stage. In-house teams make sense when you have: (1) a validated AI use case already delivering ROI, (2) ongoing work that justifies a full-time role, (3) internal capacity to manage and retain technical talent. Before that point, you're paying for learning, not for output. A consultant helps you find the validated use case first — then you can decide whether to staff it internally or keep it external. We design engagements to answer that question, not to sell you on permanent dependency.
Three things. First: do they ask about your business model and constraints before mentioning tools? If the first conversation is about GPT-4 vs Claude, walk away. Second: can they show you a clear engagement structure with defined outputs, not just "we'll figure it out together"? Third: what happens after they leave? If the answer is unclear or involves ongoing dependency, they're selling themselves, not a solution. You want someone who designs for exit.
The same way you measure any business initiative: pick one number you care about before you start, and track it. AI projects fail when they're measured by "adoption" or "engagement" instead of revenue, cost, or time. For each AI initiative, we define: (1) what metric moves, (2) by how much, (3) by when. If you can't define those three upfront, the project is an experiment — and experiments have different rules. Measure experiments by what you learn, not by ROI.
Fractalic Studio was created for founders who think in systems and are tired of vague AI promises.
Our background is in strategy, operating models, and power structures inside organisations: who actually decides, who owns which outcomes, and how processes hold under stress.
We bring that lens to AI. Tools matter, but only inside a clear frame of authority, responsibility, and measurement.
We do not promise transformation, disruption, or "reinventing your business". We commit to specific changes in how work is done and measured.
Tools are interchangeable. The system — processes, roles, decision rights — is what matters. We design for replaceable tools inside a stable frame.
Every AI workflow has an owner. If there is no clear owner on the client side, we treat the initiative as a risk by default.
Every recommendation comes with what it will cost: time, attention, political capital, and maintenance.
If an AI initiative cannot be meaningfully measured in terms the business cares about, it should not outlive an experiment.
We do not design dependence on ourselves. We build documentation, decision logs, and simple governance so the client can run the system without us.
If you're responsible for a business and want AI to be an asset instead of a distraction, let's talk.