Question 1

How long does it take to build an AI solution?

Accepted Answer

This is a decently long and iterative process. The discovery portion is the most important part. We're not going to discover what the final product looks like immediately, but we'll understand what jobs need AI tools. Typically, discovery takes 2-4 weeks, and implementation runs in 2-week sprints after that.

Question 2

What does the discovery process look like?

Accepted Answer

We practice continuous discovery, inspired by Teresa Torres' "Continuous Discovery Habits." We interview your team to understand the jobs that need doing, using frameworks like Jobs-to-be-Done mapping and a Drudgery Tax audit. We observe workflows in action, not just what people say they do. If the problem doesn't need AI, we'll tell you.

Question 3

Do you replace our existing systems?

Accepted Answer

No. We integrate with your existing tools: Slack, Salesforce, Greenhouse, QuickBooks, Jira, whatever you're using. Our AI agents work alongside your current stack, not instead of it.

Question 4

What is an Automation Blueprint?

Accepted Answer

An Automation Blueprint is a free, personalized AI automation assessment. Describe your bottleneck at supertrained.ai/blueprint and receive a diagnosis, solution paths, and ROI estimate in 60 seconds. It's our way of proving value before asking for your time.

Question 5

What AI models do you use?

Accepted Answer

We use the best tool for the job: typically Claude, ChatGPT, Gemini, Grok, or open-source models depending on the use case. For search and research, we use the best available APIs. The model matters less than how we architect the workflow around it.

Question 6

Will AI replace our employees?

Accepted Answer

No. We build AI-powered tools for humans. Humans do human things, AI does AI things. Despite all the hype, we're not seeing AI replace workers. We're seeing teams use AI to make their lives easier and focus on higher-value work.

Question 7

How do you ensure accuracy and prevent hallucinations?

Accepted Answer

We design "Human-in-the-Loop" workflows. The AI does the heavy lifting; the human does the final check. For SnowThere, we built a three-agent editorial panel that votes on every piece of content before publication. We also use structured outputs, retrieval-augmented generation, and careful prompt engineering to minimize errors. But the key is keeping humans in control of important decisions.

Question 8

How much does it cost?

Accepted Answer

Workflow automation projects start at $10K. Custom AI agent projects range from $25K to $50K. Managed AI Operations run $3K to $5K per month. Fractional AI Department engagements range from $10K to $20K per month. Every engagement starts with a discovery conversation that clarifies scope, timeline, and investment before any commitment.

Question 9

How is payment structured?

Accepted Answer

Project engagements are milestone-based: a portion at discovery kickoff, a portion at build, and a portion at deployment. This keeps both sides aligned on progress. Retainers are billed monthly. We don't ask for 100% upfront.

Question 10

Do you offer ongoing support?

Accepted Answer

Yes. We don't leave after deployment. We monitor the agents, refine the prompts, and expand their capabilities monthly. AI systems need ongoing attention -- they're more like employees than software.

Question 11

How do I get started?

Accepted Answer

Two options: Get a free Automation Blueprint for your specific bottleneck. Describe your challenge and receive a personalized analysis in 60 seconds. Or book a 30-minute Strategy Session to talk through your situation directly. No pitch deck, no sales tactics. Just a conversation.

Question 12

What industries do you work with?

Accepted Answer

We've built solutions for HR/recruiting, finance, executive strategy, and operations teams. The common thread isn't industry -- it's teams drowning in repetitive, soul-draining work who want to elevate their people.

Question 13

What if the AI makes mistakes?

Accepted Answer

It will. AI hallucinations are real and no system is immune. We design human-in-the-loop workflows where the AI handles routine work and humans make the final call on anything important. We engineer guardrails, test aggressively, and design the handoff point specifically for your risk tolerance. We build for resilience, not perfection.

Question 14

We tried automation before and it failed.

Accepted Answer

Most failures happen because teams automate before they understand the problem. We spend 2-4 weeks in discovery before writing a single line of code. If the process is broken, we fix the process first. If the problem doesn't need AI, we'll tell you.

Question 15

Isn't this just fancy Zapier?

Accepted Answer

Zapier handles "if this, then that" workflows beautifully. Our agents handle reasoning -- understanding context, making judgment calls, handling edge cases. CloneICP uses semantic search to understand what you mean, not just match keywords. SnowThere's editorial panel makes qualitative judgments about content quality. When you need intelligence and not just connections, that's where we come in. For simple automations, we'll actually recommend Zapier.

Question 16

What if we don't like the result?

Accepted Answer

Discovery includes a checkpoint before build begins. If the analysis doesn't demonstrate clear value, you can stop there. We'd rather lose a project than deliver something that doesn't work.

Question 17

Can you integrate with our specific tool?

Accepted Answer

Probably. We've worked with Slack, Salesforce, Greenhouse, Jira, QuickBooks, and 30+ other tools. If we haven't integrated yours before, we'll assess feasibility during the Automation Blueprint conversation.

Common Questions

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Common Concerns

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