Persistent memory for the models that already have it.
Clarit AI builds persistent memory infrastructure for next-generation AI models. Our flagship, Engram, is a stateful inference engine that lets AI models save and restore their internal state across sessions — replacing the wasteful practice of reprocessing entire conversations every turn.
The model has memory. The infrastructure throws it away.
Every AI conversation today restarts from scratch.
The model re-reads the entire history before responding to your next message. At 128K context, that burns 6.5 seconds of GPU compute per turn. Every turn. Every user. Every conversation.
This happens because current serving infrastructure treats model state as disposable — even when the model itself is built to preserve it. Mamba and hybrid Mamba-Transformer architectures carry compressed understanding as part of their design, but every production framework throws that state away on every request.
Engram fixes this. Two milliseconds to restore. 93.8% fewer tokens processed. Constant-size snapshots regardless of how long the conversation gets.
Where this started.
Clarit AI started with a research question in February 2026. We were exploring the landscape of truly stateful AI architectures — Google's Titans paper, IBM's Granite 4 hybrid models, the broader state-space model ecosystem — trying to understand where real memory ended and scaffolding-on-top-of-stateless-models began.
The insight came from a single observation. Mamba models already carry native compressed state in their architecture. It's genuinely there. But every production serving framework treats it as disposable overhead.
Nobody was building the infrastructure layer to preserve what these models already do.
So we forked SGLang and had a working MVP fifteen days later. That became Engram.
Billy is a builder and systems integrator with deep experience across AI infrastructure, technology consulting, and creative technology. He founded Clarit AI in 2026 to commercialize the persistent-memory infrastructure gap he identified in modern AI serving stacks.
Billy also founded and operates KHA Entertainment, an established managed services and technology consulting practice specializing in the entertainment industry. KHA provides the financial stability and operational runway that funds Clarit AI's development, letting the company build without premature dilution or accelerator dependency.
Technical credentials
- 01Architected and built the entire Engram MVP — snapshot persistence, 3-tier memory hierarchy, agent framework, REST API, WebSocket streaming, security hardening — as a 66-commit contribution merged within 15 days of project start.
- 02Contributed native Mamba2 model support for Mistral's Codestral to SGLang upstream (PR #22327), adding coverage no previous contributor had completed.
- 03Validated Engram across five production models from three major vendors (IBM, NVIDIA, Alibaba), publishing benchmark results showing 3,250× speedup at 128K context.
Strategic credentials
- 01Founder and ecosystem builder. Co-founded and built across venture, media, creator, commerce, and technology projects, including ventureLab, Kogi BBQ, GirlGamer, Ani.ME, Hawaii Bitters, and Supermassive.
- 02Product and market strategy. Experience across UI/UX, product development, digital strategy, cross-market finance, platform creation, and technology commercialization.
- 03Partnership and investor lens. Worked across startups, investors, agencies, brands, studios, and global technology ecosystems, helping translate technical products into market-facing opportunities.
Mike Prasad is a founder, strategist, designer, and product builder working across culture, technology, commerce, venture ecosystems, and digital media. At Clarit.ai, he supports technology strategy, product positioning, ecosystem development, and partnership pathways as Engram moves from validated open-source infrastructure into a broader commercial platform.
His background spans startup formation, venture ecosystems, creator platforms, digital strategy, product development, UI/UX, and emerging technology commercialization. He brings a second operator lens to Clarit.ai: technical enough to pressure-test the product direction, commercial enough to help shape the story for partners, programs, and investors.
Three deliberate operating choices.
Funding model
Bootstrap-funded by KHA Entertainment. No venture capital raised. Deliberate — it lets us build at our own pace, keep founder focus on product and distribution rather than fundraising cycles, and preserve optionality for the right strategic partner.
Distribution model
Engram is open-source. Core inference engine, snapshot persistence, and memory management layers are publicly available and actively maintained. Commercial offerings focus on the enterprise layer: multi-tenant isolation, PII redaction in model state, audit trails, SLAs.
Partnership posture
We work with hardware vendors, cloud platforms, model providers, and design partners in the coding-agent and enterprise-AI space. Active conversations are underway across each category, with announcements as agreements formalize.
The near-term roadmap.
Growing the technical team as commercial traction develops. Priorities, in order.
- 01
Model coverage expansion
Validation across 10+ Mamba hybrid architectures, including Mamba-3 research checkpoints.
- 02
Design partner engagements
First commercial deployments with coding-agent platforms and enterprise AI teams.
- 03
Enterprise tier development
Multi-tenant infrastructure for regulated industries — healthcare, finance, legal.
- 04
Ecosystem expansion
Sister products (Synapse for edge inference, Plexium for repository knowledge) extending the memory-at-every-layer thesis.
Let's talk.
For partnership inquiries, design-partner conversations, or press.Delaware C-Corporation · California