Deeptech AI
for live play.
LogitScore is a research-led deeptech AI company building confidence-aware real-time systems. Buddy is the first product, built on top of our work in logit-based confidence estimation, multimodal perception, low-latency inference, and adaptive interaction policy.
Buddy is monitoring screen, voice, and squad context.
> two enemies rotating B through mid
> smoke the cross, keep one anchor A
> confidence high, pushing cue now
Gaming is the hardest proving ground
for real-time AI.
If the assistant is late, noisy, or wrong, it breaks the session instantly. That makes gaming the right first market for a confidence-aware deeptech stack, not a side quest.
Latency kills flow
In-match copilots have to react inside the moment, not after it. If the system takes too long to listen, reason, and speak, the advice lands after the play is already over.
Wrong callouts are expensive
A bad hint is worse than no hint. In competitive play, a hallucinated callout costs trust immediately and trains users to mute the assistant.
Always-on chatter is unusable
Gamers need short, useful signal. Most assistants are tuned to keep talking, which turns live play into narration instead of support.
Cloud dependence is fragile
Real-time products cannot depend on unpredictable round trips forever. The product needs an infrastructure layer built for low-latency operation, authenticated access, and private deployment.
Buddy is built for the interaction loop where milliseconds, timing, and confidence all matter at once.
We instrument token-level logits, uncertainty bands, latency budgets, and response policy in one loop so the assistant can decide whether to speak, ask, verify, or stay silent. That is the research core as well as the product wedge.
Buddy is the first product
built on the research stack.
The product is for gamers, but the underlying work is broader: multimodal inference, confidence estimation from logits, response policy, streaming voice, and a deployment model built for product, partner, and developer use.
Quantized multimodal pipeline
Language, vision, and live context are combined in a runtime shaped for fast perception and usable throughput, not just offline quality scores.
Gameplay-aware perception
The stack combines voice, text, and screen context so the assistant can follow what is happening right now, not what happened ten seconds ago.
Logit-based confidence estimation
We read internal model signals during inference to estimate certainty in real time rather than relying on post-hoc confidence theater.
Adaptive interaction policy
Confidence is translated into behavior: answer when it is earned, ask when ambiguity matters, verify when evidence is weak, and stay silent when needed.
Streaming voice delivery
Voice output is treated as part of the system design, not a cosmetic layer, because perceived latency matters as much as model quality in live use.
Deployment and developer path
logitscore.com is the parent deeptech brand, while
buddy.logitscore.com operates as the product surface.
Buddy should not talk
all the time.
A useful gaming copilot decides whether to act at all. LogitScore turns confidence into interaction policy in real time.
Call the play.
When context is clear and confidence is high, Buddy gives a short, actionable cue instead of a long explanation.
Output: spoken callout or text cue
Ask once, precisely.
When one missing variable blocks a good answer, the assistant asks a minimal clarifying question instead of improvising.
Output: one sharp clarifying prompt
Stay quiet or verify.
If the confidence floor is not met, Buddy does not bluff. It retrieves more context, waits for a stronger signal, or simply stays silent.
Output: verification step, defer, or no interruption
Generic assistant vs. Buddy
Generic assistant
Always fills the silence.
It keeps speaking because the interface rewards output volume. Latency and uncertainty show up as noise inside the session.
Buddy on LogitScore
Acts only when it earns the turn.
It speaks, asks, verifies, or stays quiet based on explicit confidence signals. That makes the interaction tighter and more trustworthy.
State-of-the-art inference engine,
engineered for ultra-low latency.
LogitScore's core platform is a production-ready deeptech runtime. Our architecture integrates quantized multimodal perception, algorithmic confidence estimation, and dynamic interaction policies to deliver enterprise-grade performance and reliability.
runtime-architecture.png
Replace with /assets/runtime-architecture.png when the product diagram is ready
The site should show the product,
but also the skills behind it.
Buddy is the public surface. The differentiator is the research and systems work underneath: how the model perceives, scores uncertainty, decides, and responds in real time.
Research-led stack
This is not just a wrapper around foundation-model APIs. The work sits in inference behavior, uncertainty estimation, and deployable systems design.
Quantized multimodal inference
The core stack combines language and visual context in a runtime optimized for real-time use, not just large-model demos.
Confidence from logits
Confidence is estimated from the model's internal signals and tied directly to behavior, rather than being displayed as a decorative score.
Adaptive response policy
The system has to choose between answering, asking, verifying, or staying quiet. That policy layer is part of the technology, not just product copy.
Latency and voice engineering
Realtime performance includes orchestration, streaming delivery, and interaction timing, not only model inference benchmarks.
Productization and deployment
The research is productized into a runtime that supports Buddy, partner deployments, portal access, and technical integrations.
Open positions
coming soon.
We are not publishing roles yet, but the direction is clear: a small team across inference engineering, multimodal systems, product design, and developer platform. If that overlaps with your background, start the conversation early.
Contact the team.
Use this for partnerships, press, research collaboration, or early recruiting conversations. The message goes directly to the team.
contact@logitscore.com