Question 1

What does Tyigo actually do?

Accepted Answer

We're an AI-first software agency. We design, build, and scale custom software: SaaS platforms, AI applications and agents, web and mobile apps, enterprise systems, and workflow automation. Think of us as a senior product-engineering team you can plug in — from first idea to production scale.

Question 2

Who do you typically work with?

Accepted Answer

Startup founders building their first product, scale-ups adding AI capabilities, SMEs automating operations, and enterprises modernizing legacy systems. If you need world-class software shipped quickly and correctly, you're our kind of client.

Question 3

How do we start a project with you?

Accepted Answer

Book a free consultation. We'll discuss your goals, give honest feedback on feasibility, and — if we're a fit — follow up with a scoped proposal including timeline and fixed pricing. No obligation, no hard sell.

Question 4

We only have an idea, not a spec. Is that a problem?

Accepted Answer

Not at all — most of our best projects started that way. Our discovery and strategy phase turns ideas into validated scope: user research, feasibility analysis, prototypes, and a prioritized roadmap, usually within 1–2 weeks.

Question 5

How long does a typical project take?

Accepted Answer

An MVP typically ships in 6–10 weeks. Larger platforms run 3–6 months to first production release, then continue in iterative phases. We scope for the fastest path to real users, because feedback beats speculation.

Question 6

How will we communicate during the project?

Accepted Answer

A shared Slack channel, a weekly live demo of working software, and a project board you can see (and reprioritize) at any time. You'll never wonder what's happening with your budget.

Question 7

Can you work with our in-house team?

Accepted Answer

Yes — we regularly embed with internal teams: pairing with your engineers, following your code review process, and transferring knowledge as we go. We also do the inverse: leading delivery while your team focuses elsewhere.

Question 8

What happens if requirements change mid-project?

Accepted Answer

They usually do, and our process expects it. Work is organized in short sprints with a re-prioritizable backlog. Small changes flow into sprints naturally; significant scope changes get explicitly re-estimated so budget decisions stay in your hands.

Question 9

Do you offer design services, or only development?

Accepted Answer

Both, and they're better together. Our design practice covers user research, UX, high-fidelity UI, and design systems. Most engagements pair designers and engineers on one team, eliminating handoff loss.

Question 10

How much does a project cost?

Accepted Answer

Most MVPs land between $25K and $75K; larger platforms range $100K+. Every project gets a custom quote after a scoping conversation. We quote fixed-price for fixed scope, so there are no billing surprises.

Question 11

Do you work on a retainer basis?

Accepted Answer

Yes — after launch, most clients continue with a monthly product retainer covering feature development, maintenance, and support. Retainers start at a fixed monthly capacity you can scale up or down with notice.

Question 12

Do you sign NDAs?

Accepted Answer

Of course. We're happy to sign your NDA before any detailed conversation, and confidentiality terms are standard in our contracts.

Question 13

What if we're not satisfied with the work?

Accepted Answer

Weekly demos mean problems surface in days, not months — you course-correct while it's cheap. Contracts are structured in phases with clear deliverables, and you can exit at any phase boundary with everything built so far, fully documented.

Question 14

Which AI models and providers do you use?

Accepted Answer

Anthropic Claude, OpenAI GPT, Google Gemini, and open-source models — chosen per use case for quality, cost, and data requirements. We build provider-agnostic abstractions so you can switch models as the landscape evolves.

Question 15

How do you handle AI accuracy and hallucinations?

Accepted Answer

With engineering, not hope: retrieval-augmented generation grounded in your data, output validation, citation requirements, automated evaluation suites, and human review gates where stakes are high. We measure quality before and after every change.

Question 16

Is our data safe when used with AI models?

Accepted Answer

Yes. We use enterprise API tiers where prompts aren't used for training, apply data minimization and PII redaction in pipelines, and can deploy within your cloud perimeter or with EU data residency when compliance requires it.

Question 17

What's your default technology stack?

Accepted Answer

TypeScript and Next.js on the frontend; Node.js or Python (FastAPI) backends; PostgreSQL; Terraform-managed infrastructure on AWS, GCP, or Azure; and the modern AI stack (Claude, LangChain, vector databases). We adapt to your existing stack when there is one.

Question 18

Who owns the code and intellectual property?

Accepted Answer

You do — completely. All code, designs, documentation, and infrastructure configuration are delivered in your repositories and accounts. Full IP assignment is written into our standard contract.

Question 19

Do you provide support after launch?

Accepted Answer

Yes. Every launch includes a stabilization period, and ongoing support contracts cover monitoring, incident response with defined SLAs, security patching, and continued feature development.

Question 20

Can you take over a project from another team or agency?

Accepted Answer

Yes, we do rescues regularly. It starts with a code and infrastructure audit (typically 1–2 weeks) producing an honest assessment: what's solid, what's risky, and a stabilization plan. Then we take ownership incrementally without a risky big-bang rewrite.

Questions, Answered Honestly

Getting Started

Process & Delivery

Pricing & Contracts

Technology & AI

Support & Ownership

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