Question 1

What kind of projects does SDEN take on?

Accepted Answer

We work across the full AI journey: training your teams, auditing where agents are worth it, and designing, building, and running the AI agents, platforms, and apps that result, with the cloud and security underneath. Every engagement is scoped so your team can own and run what we build, rather than depend on us.

Question 2

What does an engagement with SDEN look like?

Accepted Answer

In four phases: scoping and architecture, design and prototyping, development and hardening, then delivery and support. You validate the direction on something concrete at every step, and we stay committed after the production release.

Question 3

Do you work on existing projects or only from scratch?

Accepted Answer

Both. We design products from a blank page, and we also take over, audit, and rebuild existing codebases, starting by laying down a sound architecture.

Question 4

How do you guarantee code quality and security?

Accepted Answer

Systematic code review, automated tests, security built in from the design stage (encryption, access control, data isolation), and no technical debt left behind. Security isn't a step. It's an engineering discipline.

Question 5

Who owns the code and the intellectual property?

Accepted Answer

You do. The code produced during an engagement is entirely yours: repositories, documentation, and operational access are transferred on delivery.

Question 6

What proves your level of engineering?

Accepted Answer

Our own products. SDEN designs, builds, and operates its own SaaS products in production: Real Estate, Lead Manager, Beauty, and University Portal. The most direct demonstration of what we can build for our clients.

Question 7

What is an agentic engineering partner, and how is SDEN different from an AI consultancy?

Accepted Answer

An agentic engineering partner designs, builds, and runs production AI agents (software that plans, uses tools, and completes multi-step work) plus the systems around them: evals, guardrails, monitoring, and fallbacks. SDEN owns the full stack (AI, software, security, cloud) under one senior team, takes agents through production, and hands you the code and the operational knowledge so your team runs them without us. A consultancy stops at advice; we ship and hand over.

Question 8

Should we build AI agents in-house, hire an engineering partner, or buy off the shelf?

Accepted Answer

Buy when an off-the-shelf tool already solves it and its data handling fits your constraints. Build in-house when the agent's logic is core to your product and you have senior engineers who have shipped agents before. Hire a partner when the agent is load-bearing, the cost of failure is high, and you want your team to own it afterward. Every SDEN engagement starts with that build-versus-buy call, and we will tell you to buy when buying is right.

Question 9

How do you keep a production AI agent from becoming a black box?

Accepted Answer

The code lives in your repositories from the first commit, the IP transfer is in the contract, and every build ships with documentation, runbooks, and monitoring written for the next engineer on your team. We operate the agent jointly with your team through a support window so the knowledge transfers, then we step back. No black box, no dependency dressed up as a retainer.

Question 10

How do you stop an AI agent from hallucinating or running up costs?

Accepted Answer

By design first: agents work over grounded data (RAG) and explicit tool schemas, not free-form prompting. Then evals: every agent ships with a test harness that measures success before it goes live. Then runtime controls: guardrails on inputs and outputs, hard cost ceilings so a runaway loop cannot bankrupt the feature, and monitoring of quality, drift, and spend in production, not just uptime.

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