Question 1

What is Fraktional and who is it for?

Accepted Answer

Fraktional gives startups, mid-market companies, and private organizations a fractional CTO/CISO and the engineers to go with it. We build AI products and infrastructure, integrate AI into existing systems, and make build-vs-buy calls. We come from security engineering, so the work holds up to a real audit, and our own agent, Kai, works every engagement alongside our senior engineers. We’re not a SaaS. Everything we build is tailored to you and lives in your infrastructure. We also run compliance audits and pentests when teams need them.

Question 2

We don’t have an engineering team. Can you still build for us?

Accepted Answer

Yes. Many of our clients are startups and mid-market businesses without an in-house engineering org. Your fractional CTO/CISO owns the technical decisions, our forward-deployed engineers build and run the system, and everything lands in accounts you control. When you’re ready to bring it in-house, we help you hire and onboard the team that takes over.

Question 3

Can you audit what we already have before building anything?

Accepted Answer

Yes, and many engagements start exactly there. We audit your whole operation: infrastructure, access, vendors, data flows, and how AI is already being used. Our own agents do the sweeping, which is why it takes days instead of quarters, and a senior engineer pilots the work and signs every finding. You get a prioritized list, we fix what we found, and we harden the system. Only then do we build new things on top. If all you want is the audit, that’s a deliverable on its own.

Question 4

Can you help us adopt AI safely?

Accepted Answer

Yes. We help teams roll out Claude Code, Cursor, Copilot, or custom internal AI tools. We set up data boundaries, access controls, review policies, and the training that keeps adoption from going sideways. If your engineering team wants to move and your security team is asking hard questions, we bridge that gap.

Question 5

Do we own the code and infrastructure?

Accepted Answer

Yes. We’re not a platform. Every system we build runs in your environment, owned by you. We can operate it with you, or we can help you hire and onboard the in-house team that will. You can walk away with everything. No lock-in. No per-seat fees.

Question 6

Can you help us replace a legacy vendor with an in-house system?

Accepted Answer

Yes. Modern AI tools changed the math on build vs. buy. Teams that used to sign with vendors are now building in-house systems they own. We help you evaluate the tradeoffs: your team, your timeline, your maintenance appetite, and the real cost. Then we give you a defensible call. If the answer is build, we can build it with you or help you hire the team that will. We also set up the evals and monitoring that keep the new system safe and working in production.

Question 7

Can you actually build AI features alongside our engineers?

Accepted Answer

Yes. We write production code alongside your team. LLM features, agents, RAG, evaluation pipelines. Your engineers stay in the loop and inherit everything. When we’re done, your team can keep building, and the system lives in your repos and your infrastructure.

Question 8

How do you handle data security with LLM providers?

Accepted Answer

Every engagement starts with data boundaries. We configure zero-retention endpoints where providers support them. We design prompt scrubbing and PII controls into the pipeline. We document what data leaves your environment and why, so your security and legal teams can sign off. When a model provider won’t meet the bar, we help you pick one that will or run the model privately.

Question 9

How do you handle confidentiality? Will you work under NDA?

Accepted Answer

Every engagement runs under NDA by default, and for high-sensitivity work we sign your paper, not the other way around. We never name clients, use logos, or publish case studies; the archetypes on this site are illustrative for exactly that reason. The work happens in your accounts with scoped, revocable access, and what we learn about your business stays inside the engagement.

Question 10

What is ISO 42001 and do we need it?

Accepted Answer

ISO 42001 is the international management standard for AI systems. It covers governance, risk, data, and monitoring for the AI you deploy. You need it if your customers are asking how you govern AI, if you operate in regulated sectors, or if you want to get ahead of AI procurement questions before they become blockers. We can certify you against it end-to-end.

Question 11

How is this different from hiring a traditional security consultant or AI agency?

Accepted Answer

Traditional security firms staff with junior analysts and take quarters. AI agencies ship features but don’t ask the security questions. We do both. Senior engineers who have actually shipped AI at scale, with the security rigor to keep it defensible. You get one team, not two contracts.

Question 12

How long does an engagement take?

Accepted Answer

It depends on scope. A full security and AI audit runs 2 to 4 weeks. An AI tooling rollout takes 2 to 4 weeks. A build-vs-buy advisory sprint is usually 1 to 2 weeks. Shipping an AI product feature is typically 4 to 8 weeks. A SOC 2 readiness assessment takes 2 to 4 weeks. We’ll give you a specific timeline during the scoping call.

Question 13

How does pricing work?

Accepted Answer

Every engagement is scoped to you, because the work is specific to your systems, your data, and your compliance picture. After the scoping call you get a fixed quote for a fixed scope: one number for an audit or a build, one monthly number for a retainer. No hourly billing surprises, no seat licenses, no overage fees.

Question 14

How do you handle AI accuracy and trust in your own work?

Accepted Answer

Every deliverable goes through senior engineer review before you see it. We do not ship raw AI output. The AI is our tool, not your deliverable.

Questions, answered straight.

The answers, before you ask.

Questions, answered straight.

The answers, before you ask.

01What is Fraktional and who is it for?+

02We don’t have an engineering team. Can you still build for us?+

03Can you audit what we already have before building anything?+

04Can you help us adopt AI safely?+

05Do we own the code and infrastructure?+

06Can you help us replace a legacy vendor with an in-house system?+

07Can you actually build AI features alongside our engineers?+

08How do you handle data security with LLM providers?+

09How do you handle confidentiality? Will you work under NDA?+

10What is ISO 42001 and do we need it?+

11How is this different from hiring a traditional security consultant or AI agency?+

12How long does an engagement take?+

13How does pricing work?+

14How do you handle AI accuracy and trust in your own work?+