← Abaka AI
Abaka AI role-play cheat sheet
For the mock cold call at the end of most SDR interviews.
What they sell, in one line
Provides high-quality data collection and annotation services that AI companies use to train their models.
Who you'd be calling
Heads of Data, ML or AI Engineering leads, and Product leaders at AI labs, AI startups and automotive AI teams
Your opener
“Hi [Name], this is [Your Name] from Abaka AI. We help AI teams get training data faster. Do you have a minute for me to ask how you handle data labeling today?”
Problems you solve for them
- Models need large amounts of accurate, labeled training data
- Building an in-house annotation team is slow and costly
- Poor data quality leads to weaker model performance
Discovery questions to ask
- Where does your training data come from today?
- What's the biggest bottleneck when you scale up data labeling?
- How do you check data quality before it goes into training?
Objections they'll throw at you
“I'm busy right now.”
→ No worries, I'll keep it short. Is there a better time this week for a 10-minute chat about your data pipeline?
“Not interested.”
→ Understood. Is data sourcing something your team already has fully handled, or just not a focus right now?
“We already have a data vendor.”
→ Great, you've got a process. How is that vendor doing on speed and quality when your volumes go up?
“Just send me an email.”
→ Happy to. What type of data matters most to you, so I send something relevant?
Competitors worth knowing
Scale AI, Surge AI, Appen
Interview tips for this company
- Understand simple terms: training data, annotation, labeling, and what an AI model needs them for.
- Read up on the AI data industry so you can talk about why data quality matters.
Written from public information about Abaka AI to help you practice. Ask an insider what their role play looked like; it's the best prep there is.