Question 1

What does Feather Studio build?

Accepted Answer

We design and engineer AI-native products, enterprise agent systems, and applied AI workflows. We launch new products, add AI capabilities to existing software, and deploy agents into the systems teams already use.

Question 2

Do you work with startups or enterprises?

Accepted Answer

Both. For startups, we shape and ship AI-native products. For enterprises, we work alongside internal teams to deploy agent systems and new AI capabilities within existing architecture, security, and operating constraints.

Question 3

Can you work alongside our internal team?

Accepted Answer

Yes. We can work as an embedded product and engineering team or own a defined deployment. Product, engineering, security, and operations leaders stay close to the decisions that matter.

Question 4

How does an engagement begin?

Accepted Answer

A focused working session maps the workflow, systems, constraints, and measurable outcome. We then recommend the smallest production path worth pursuing, with clear scope, timing, and investment.

Question 5

How quickly can we get to production?

Accepted Answer

A focused prototype can take a few weeks. Production timelines depend on integrations, data access, evaluations, permissions, and change management. We define those constraints before committing to a schedule.

Question 6

How will we see progress?

Accepted Answer

We work in short delivery cycles with visible prototypes, working software, and explicit decisions. You see the system evolve throughout the engagement, not just in a final presentation.

Question 7

Can you connect AI to our existing systems?

Accepted Answer

Yes. We design around your current APIs, data sources, identity layer, approval paths, and operational tools. A platform migration is only proposed when it creates a clear business or technical advantage.

Question 8

Are you tied to a specific AI model or vendor?

Accepted Answer

No. We select models and infrastructure based on the job, quality requirements, latency, cost, privacy, and your existing stack. We also design for model changes when vendor flexibility is important.

Question 9

How do you handle security and sensitive data?

Accepted Answer

Security is addressed during architecture, not after launch. We define data boundaries, access controls, logging, human approvals, and fallback behavior with your team before consequential workflows go live.

Question 10

Do you offer fixed pricing?

Accepted Answer

We price around the outcome and delivery risk. Focused sprints can usually be fixed-scope, while larger builds may use phased or ongoing engagements. Every proposal makes deliverables, schedule, and investment explicit.

Question 11

Who owns the product and code?

Accepted Answer

You do. Unless a different arrangement is agreed in writing, the custom product, source code, designs, and project deliverables created for your engagement transfer to your company.

Question 12

What happens after launch?

Accepted Answer

We can continue with monitoring, iteration, reliability improvements, and workflow expansion, or hand the system to your internal team with documentation and a structured transition.

We design and build AI-native products and systems.

Built for real work, not the pitch deck.

CareerCrew OS

CareerCrew

FlightFare

CareerCrew OS

CareerCrew

FlightFare

From the right opportunity to production.

Choose the right opportunity.

Prove the value early.

Build into the operation.

Keep it useful.

Before we begin.

We design and build AI-native products and systems.

Built for real work, not the pitch deck.

CareerCrew OS

CareerCrew

FlightFare

From the right opportunity to production.

Choose the right opportunity.

Prove the value early.

Build into the operation.

Keep it useful.

A senior team from first decision to production.

AI-native delivery

Product and engineering together

Built for production

Fits the operation

Before we begin.