Investors
Why this, why now, why us.
The short version: the demand was always there, the technology just crossed the line where it stops feeling like a translation tool and starts feeling like a conversation.
- Median end-to-end latency
- 420 msMedian end-to-end latency
- Languages at launch
- 32Languages at launch
- Cost advantage vs. on-site interpreting
- 11×Cost advantage vs. on-site interpreting
Thesis
Four claims we are betting on.
The market was never the problem
Interpretation and translation services are a multi-billion-dollar industry that runs on scheduled human labour. Every one of those bookings exists because two people could not simply talk. The demand has never needed proof.
What changed is the latency floor
Streaming recognition, speculative decoding and on-device synthesis independently crossed usable thresholds in the last eighteen months. Composed carefully, they land under the half-second mark where an exchange still feels like a conversation. That was not true two years ago.
Software gets us in the room. Hardware keeps us there.
A phone app proves the value and builds the usage data. The defensible position is the device — microphone array, on-device inference, all-day operation — plus the domain glossaries and workspace context that accumulate per customer and do not transfer.
Distribution is bottom-up, then top-down
Individuals adopt it at trade shows and on trips. Teams standardise on it when someone notices the interpreter line item. Enterprises sign when residency, SSO and an SLA are on the table. Each layer funds the next.
We are selective about capital, and open about why.
Hardware timelines punish investors who need a quick mark. If that is not you, write to us — the deck, the latency benchmarks and the unit-economics model are available under NDA.
investors@babelgo.ai