Comment on page
Twig v/s Build In-house?
Can you build an In-house AI solution for your B2B CX teams
Can I build an AI in-house? Often we see engineers build demos and cool hackathon projects that showcase how internal data can be used to create an AI. The question CX leaders face is do they build and fund an internal initiative and how this will pan out over time.
I have to prioritize the AI needs of our customers vs. internal solutions. Even if we were to build internally, we could at most do one iteration but not provide continued updates. The cost of using our internal data scientists and engineers to build such a solution would be over $1M USD over 2-3 years. - Head of AI at Major Software SaaS Platform
.png?alt=media&token=e804832e-f399-44de-a046-4e3fbae521a6)
Enterprise Needs | Twig | Home Grown Solution |
|---|---|---|
Time to value | Most customers are fully live within 2 weeks | It takes 4-6 months to build a full solution from a hackathon project or demo. |
Product Updates | Twig publishes product updates every week | Engineers get re-assigned to new projects and the AI stops to improve |
Depth of solution | Twig works with B2B customers, we constantly learn from customer needs and develop deep solutions | Often limited by exposure to only one CX team and engineering teams' bandwidth to continue to innovate. |
Risk of losing developers | As a company that builds AI solutions we are able to hire and retain the best talent | Team members who built the AI solution are most likely to leave and join AI startups. |
Last modified 2mo ago