🤔 Why TotemXLabs Questions

Why should we choose TotemX Labs over hiring an in-house AI team?

Startups face challenges in hiring, retaining, and scaling AI talent. With TotemX Labs, you get:
✅ Instant access to senior AI experts (without long hiring cycles)
✅ Faster AI development with a streamlined execution model
✅ No overhead costs (salaries, benefits, hiring risks)
✅ Scalable engagement (we grow as you grow)

We act as your plug-and-play AI team—whether you need a rapid AI pilot, full-stack AI development, or strategic guidance.

What’s your experience with startups?

We have built and scaled AI solutions for early-stage startups to enterprise clients. Our expertise spans:
✅ MVP-stage AI (turning an idea into a working prototype)
✅ AI feature integration into existing SaaS products
✅ Scaling AI solutions for real-world production environments

Unlike traditional consulting firms, we own the execution and deliver working AI solutions—not just slide decks.

What’s the best way to engage with TotemX Labs?

We offer three flexible models, depending on your needs:

1️⃣ AI Pilot (3-6 months) – Ideal for startups exploring AI feasibility
2️⃣ Fractional AI Team – We integrate with your team & accelerate development
3️⃣ Full AI Product Development – End-to-end AI model design, training, deployment

💰 Cost & Budget

How much does AI development cost?

Pricing depends on:
✅ Scope (simple AI model vs. full-stack AI product)
✅ Infrastructure needs (cloud, GPUs, data pipelines)
✅ Engagement model (advisory vs. hands-on development)

💡 Typical engagement ranges:

• AI POC (3 months) → $30K – $80K
• MVP AI product (6 months) → $80K – $200K
• Full AI integration (1 year) → Custom pricing

We ensure cost efficiency by leveraging pre-built AI components and optimizing cloud expenses.

How do we control AI costs?

We optimize for business impact, not just AI hype:
✅ Early validation – Avoid costly experiments with no ROI
✅ Pre-built AI modules – Reduce dev time & costs
✅ Lean infrastructure – Optimize cloud & GPU usage

💡 Example: One startup reduced their AI cloud costs by 86% after we redesigned their infrastructure.

⚙️ Execution & Process

What do you need from us to start an AI project?

To move fast, we require:
✅ Business problem clarity (What do you want AI to solve?)
✅ Data access (Do you have training data, or do we need to generate it?)
✅ Product roadmap alignment (How will AI integrate into your business?)

We’ll guide you through a structured Discovery Phase to refine your AI strategy before coding starts.

What if we don’t have AI expertise in-house?

No problem! We provide:
✅ End-to-end AI execution (strategy, development, deployment)
✅ Knowledge transfer & documentation for internal teams
✅ AI hiring support if you want to build your own AI team later

Think of us as your fractional AI CTO—handling the hard AI work while you focus on growth.

How long does it take to build an AI product?

🔹 Proof of Concept (POC): 4-8 weeks
🔹 MVP (Minimal Viable AI Product): 3-6 months
🔹 Full-Scale AI System: 6-12 months

We use agile sprints to ensure fast iterations & business alignment.

How do you handle changing priorities & fast pivots?

We operate in agile mode—just like your startup.
✅ We adjust sprint goals based on business impact
✅ We focus on “must-have” vs. “nice-to-have” AI features
✅ We provide weekly progress updates & strategy realignment if needed

We never over-engineer AI—only build what delivers value.

🔄 Long-Term Support & Scalability

What happens after the AI pilot?

If successful, you have three options:
1️⃣ Scale the AI solution (We optimize & expand functionality)
2️⃣ Transition AI in-house (We train your team & hand over development)
3️⃣ Ongoing AI partnership (We continue as your AI R&D team)

We ensure zero vendor lock-in—you always own the code & models.

Will you help us transition AI in-house?

Yes! If you plan to hire an internal AI team, we provide:
✅ AI hiring support (job descriptions, candidate screening)
✅ AI model handover & documentation
✅ Training for engineers & product teams

We help de-risk AI adoption so you can build in-house AI capabilities at the right time.

What industries do you specialize in?

We have worked with SaaS, Healthcare, Marketing, Finance, Law, Manufacturing, Environment, Media and Education startups, applying AI in:

• LLM & Generative AI (custom LLMs, chatbots, AI copilots)
• Predictive Analytics (AI-driven forecasting & insights)
• AI Automation (reducing manual workflows with AI-powered decisions)

 

🚀 What should you bring? a.k.a. Startup Readiness Checklist for AI Pilot

1️⃣ Business & Product Inputs

✅ Clearly defined AI use case (problem statement, expected impact)
✅ Product Requirement Document (PRD) with user journey & business goals
✅ Key performance metrics (KPIs for success, e.g., accuracy, speed, cost reduction)
✅ Competitor/benchmark analysis (if applicable)
✅ List of stakeholders & decision-makers

2️⃣ Data & Engineering Inputs

✅ Sample dataset (CSV/JSON/DB connection) for initial testing
✅ Data schema documentation (fields, formats, dependencies)
✅ Data compliance & security policies (GDPR, HIPAA, etc.)
✅ Data refresh rate & availability (batch vs. real-time)
✅ Access credentials (DB queries, APIs, cloud storage)

3️⃣ Infrastructure & DevOps Setup

✅ Cloud provider access (AWS, GCP, Azure)
✅ Compute resources available (GPUs, TPUs, storage)
✅ DevOps support contact (point of contact for infra issues)
✅ Access to version control (GitHub, GitLab, Bitbucket)
✅ CI/CD pipeline details (if relevant for deployment)

4️⃣ Collaboration & Decision-Making Process

✅ Main POC from startup (Product Owner, CTO, AI lead)
✅ Preferred communication tools (Slack, Teams, Notion, etc.)
✅ Project management tool access (Jira, Trello, Asana)
✅ Weekly check-in schedule confirmed (async or live)
✅ Approval process documented (who signs off what)

5️⃣ Long-Term Vision & Handoff Strategy

✅ Plan for scaling AI post-pilot (continue agency vs. build in-house)
✅ Budget & timeline estimates for Phase 2
✅ Hiring plan (if transitioning in-house)
✅ Knowledge transfer expectations (if agency exits after pilot)

⛹🏻‍♀️ How Do We Get the Ball Rolling!

1️⃣ Startup finalizes and shares PRD, datasets, and access credentials.
2️⃣ Agency sets up an initial environment and develops proof-of-concept (PoC).
3️⃣ AI pilot officially kicks off with weekly progress updates.