We turn what the market is asking for into applied research.
TIIF sees real demand before anyone builds for it. We take the hardest of those problems into R&D, co-researching with a dedicated AI lab, and turn what proves out into the infrastructure our ventures run on.
We listen to the market
TIIF sits at the top of the funnel across ventures, operators, and agencies. We see what people are actually asking for before it shows up in a roadmap, and we bring those signals into research.
We research with the Lab
We partner with an independent research collective to take the hard problems past a demo: real accuracy on real data, real cost at scale, real reliability. Research-first, with documented outputs.
We ship what proves out
What survives the research becomes shared studio infrastructure, the spine every TIIF venture builds on. R&D isn't a side lab; it's how the stack keeps compounding.
Co-researching with the Applied AI Systems & Reliability Lab.
We partner with the Applied AI Systems & Reliability Lab, an independent technical research collective focused on safe, reliable, and cost-conscious AI for organizations with real-world constraints. TIIF brings the demand signal, the use cases, and the path to market; the Lab brings rigorous evaluation, reliability testing, and deployment research. The Lab keeps a strict firewall between its research and any commercial work, so the science stays honest and the outputs stay published.
The frontier we think opens the most doors.
AI that runs close to the user unlocks applications and businesses that hosted-only models can't reach.
Local AI
Models that run on-device and at the edge, opening up whole classes of applications and businesses that can't depend on a round-trip to a hosted API.
AI on mobile
Getting real capability onto phones, where the users already are, within tight memory, battery, and latency budgets.
Privacy-first AI
Architectures where sensitive data never has to leave the user's control, so AI is viable in regulated and compliance-heavy sectors.
Initiatives we're working on today.
Serverless RAG on AWS
Retrieval-augmented generation with no servers to run: an event-driven, pay-per-use pipeline on the AWS cloud that indexes, retrieves, and grounds answers, and scales to zero when idle.
Serverless ASR
Automatic speech recognition delivered the same way: transcription that spins up on demand, costs nothing at rest, and stays affordable at scale.
AI deployment on mobile
Packaging and running models directly on mobile devices, quantized and optimized to fit the constraints, so inference happens on the phone instead of a data center.
Have a hard problem worth researching?
If you're an operator or business sitting on a problem that needs real R&D, not just a wrapper, we'd like to hear it.