Question 1

What is the difference between Automation and Agentic AI?

Accepted Answer

Automation follows a script (if X, then Y). Agentic AI follows a goal (Achieve X). Agents can reason, plan, adapt to errors, and use tools to accomplish complex objectives without needing a predefined path for every step.

Question 2

Will AI agents replace my human team?

Accepted Answer

No. We believe in "Human-in-the-Loop" systems. Agents handle the repetitive, high-volume cognitive labor, freeing your human experts to focus on strategy, creativity, and high-level decision making.

Question 3

Why do you call it "AI-Native Delivery"?

Accepted Answer

Traditional software development is slow and manual. We use AI agents to write code, generate tests, and deploy infrastructure. This allows us to move at 10x the speed of traditional consultancies.

Question 4

How fast can you deliver an MVP?

Accepted Answer

With our Agentic approach, we typically deliver functional MVPs in 4-8 weeks. By automating the boilerplate and infrastructure setup, we focus 100% of our time on your unique business logic.

Question 5

Who owns the code and the models?

Accepted Answer

You do. Unlike SaaS platforms where you rent your capabilities, we build assets that you own. The code, the fine-tuned models, and the data pipelines are 100% your intellectual property.

Question 6

What is the "SaaS Trap"?

Accepted Answer

The SaaS Trap is the danger of relying too heavily on rented third-party tools for your core business logic. It leads to data silos, rising costs, and a lack of competitive advantage.

Question 7

How do you handle data privacy?

Accepted Answer

We deploy Private LLMs and RAG systems within your own cloud environment (AWS, Azure, GCP). Your data never leaves your controlled perimeter to train public models.

Question 8

What is the typical ROI?

Accepted Answer

Our clients typically see a 300% ROI within the first 12 months. This comes from a combination of reduced operational costs (via automation) and increased revenue velocity (via faster time-to-market).

Question 9

How does Agentic AI comply with the EU AI Act?

Accepted Answer

We build "High-Risk" ready systems with explainability, human oversight, and rigorous testing logs by default. Our "Glass Box" architecture ensures every decision is traceable and audit-ready for regulators.

Question 10

Can agents work with our 20-year-old mainframe?

Accepted Answer

Yes. We build "Agentic Wrappers" (APIs) around legacy systems, allowing modern agents to interact with them safely without rewriting the core.

Question 11

What happens to my junior developers?

Accepted Answer

They become "AI Architects." Instead of writing boilerplate, they review agent code, design system prompts, and manage agent performance. Their output multiplies by 10x.

Question 12

What if OpenAI raises their prices?

Accepted Answer

Our "Model Agnostic" architecture allows you to swap LLMs (e.g., from GPT-4 to Claude 3 or Llama 3) with a single config change. You are never locked into one provider.

Question 13

How do we prevent runaway API costs?

Accepted Answer

We implement "Token Budgets" and "Router Agents" that route simple tasks to cheaper models (like Haiku/Flash) and only complex reasoning to expensive ones (like Opus/GPT-4).

Question 14

Is this just hype, or is it ready for production?

Accepted Answer

It is production-ready. We have agents running critical workflows in FinTech and Healthcare today, processing millions of transactions with higher accuracy than humans.

Question 15

Why build custom agents instead of buying SaaS?

Accepted Answer

SaaS forces you to adapt your process to their software. Custom agents adapt to YOUR unique process, giving you a defensible competitive advantage that competitors can't just buy off the shelf.

Question 16

How do we scale from a pilot to the whole enterprise?

Accepted Answer

We use "Agentic Swarms" and Kubernetes-based orchestration. Agents are stateless and containerized, allowing infinite horizontal scaling as workload increases.

Question 17

How do we manage the cultural shift?

Accepted Answer

We start with "Co-pilot" mode (human approves all actions) to build trust, then graduate to "Autopilot" (human reviews exceptions) as confidence grows.

Question 18

Will my competitors have this too?

Accepted Answer

Eventually, yes. But the "Data Moat" you build today—by capturing your unique business logic in agent workflows—will be the uncopyable asset that keeps you ahead.

Question 19

What is "The New Enterprise Standard"?

Accepted Answer

It represents the shift from "Digital Native" (cloud/mobile) to "AI Native" (agentic/autonomous). It means businesses run at machine speed, with decision-making decentralized to AI agents under human strategic oversight.

Question 20

What does "AI-Native" actually mean?

Accepted Answer

It means AI isn't a feature; it's the foundation. We don't just add a chatbot to your app; we rebuild your core workflows so that AI agents are the primary drivers of execution.

Question 21

What are the "Three Pillars" of the AI-Native Way?

Accepted Answer

1) Intent-Based Engineering: You define the goal, agents write the code. 2) Agentic Operations: We manage agent fleets. 3) Sovereign Intelligence: You own the models and the data.

Question 22

Why adopt the AI-Native Way now?

Accepted Answer

Because the cost of intelligence is collapsing. Companies that stick to manual, human-heavy workflows will be outpaced by competitors who can execute 100x faster at 1/10th the cost.

Question 23

How do we implement the "Three Pillars"?

Accepted Answer

We start by mapping your "Intent" (business goals). Then we deploy "Agentic Pods" to build the solution (Engineering). Finally, we set up "AgentOps" to monitor and refine the system (Operations).

Answers for the
Agentic Age.

What is the difference between Automation and Agentic AI?

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Answers for the Agentic Age.

What is the difference between Automation and Agentic AI?

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Answers for the
Agentic Age.