Graphon Labs, an applied AI lab building Persistent Intelligence to power the next generation of AI agents and accelerate progress toward AGI, today announced a $35 million Series A led by RRE Ventures, with participation from HP, Energy Impact Partners, Hitachi Ventures, and Gaia VC.
Persistent Intelligence enables AI to continuously access, understand, remember, and build upon everything that came before. Graphon Labs is building the foundational infrastructure to make this possible at scale, unlocking a critical capability on the path to AGI. As AI evolves from models that answer questions to agents that run around the clock, the ability to retain context, learn from experience, and accumulate knowledge over time becomes essential.
“Models can reason, and agents can act, but neither gets better if they cannot build off of prior knowledge,” said Raju Rishi, General Partner at RRE Ventures. “Graphon Labs lets intelligence accumulate which can have profound impacts upon efficacy, compute time, complexity of queries, and much much more. We see it becoming the source of truth beneath every agent, and that’s why we led this round.”
The round comes less than six months after Graphon Labs emerged from stealth with $8.3M in seed funding. The raise accelerates the research and infrastructure needed to expand Persistent Intelligence beyond enterprise deployments to developers and devices, ultimately making it available to everyone.
Graphon Labs went a different direction to build towards AGI
The frontier labs in the industry have spent billions making models smarter, but even the most capable models and agents forget. RAG, GraphRAG, context windows, and traditional retrieval architectures can retrieve information, but they compress, fragment, or lose important context, relationships, history, and temporal understanding as information grows and changes.
Graphon Labs started from a different question: what infrastructure does intelligence need to keep learning from everything that came before? Its answer is built on graphons, a mathematical framework for analyzing very large graphs, which Graphon Labs’ founders developed during their PhDs.
“The world is heading toward agents and physical systems that create and depend on more information than anyone has ever had to manage,” said Graphon Labs Founder and CEO Arbaaz Khan. “In a world where we are moving to AI using computers, we need to fundamentally rethink how computers access data to pre-fill their context windows. The old way, using vector search, is like searching through the pages of a torn-up book. We take those pages and turn them into a connected map, unlocking seamless memory search.”
It rethinks each layer of the stack, across storage → search → retrieval → reasoning → memory. The result preserves what an agent knows, what it has done, what changed, and what happened as a result, with relationships, sources, and timing intact. It also cuts the compute time it takes to represent and reason across enormous amounts of information.
Graphon achieved the highest accuracy among evaluated systems on three leading benchmarks for long-term context: LoCoMo, ConvoMem and ATM-Bench.
On LoCoMo, Graphon scored 93.9% accuracy using 58% fewer tokens than loading the full conversation into the model. On ConvoMem, it achieved 90.2% accuracy with 95% fewer tokens. On ATM-Bench, a benchmark from researchers at the University of Cambridge testing question answering across video, audio, images and text, Graphon scored 81.7%, 5.0 percentage points ahead of the next system on the public leaderboard. LoCoMo and ConvoMem comparisons use baseline results published by Databricks.
Beyond academic benchmarks, Graphon Labs’ technology is applicable in production to a wide swath of industries.
“At the 49ers, we’re always looking for innovative ways to strengthen our business and drive growth,” said Costa Kladianos, EVP of Technology for the San Francisco 49ers. “From uncovering new sponsorship opportunities to empowering our teams, we’re excited to explore how Graphon Labs’ technology can help us gain a competitive edge.”
“At Hitachi Rail, we seek to unlock greater value from complex and distributed information landscapes, often with mission-critical operational outcomes,” said Amaury Jourdan, Deputy Manager and CTO for Digital and AI Activities at Hitachi Rail. “Our evaluation of Graphon Labs’ innovative technologies shows promise to facilitate the discovery of context knowledge, automate the connection to data sources and improve AI inferencing results in our specific industrial context.”
One architecture for everyone
The next generation of agents will run continuously. They will need to remember what happened yesterday, understand what changed today, learn from prior actions, and carry that knowledge into tomorrow. Agents that can reason and act still have to remember before they can learn, and that step is what turns them into Persistent Intelligence.
Graphon Labs is building one intelligence architecture that scales from the enterprise to the individual. The goal is for it to sit beneath agents wherever intelligence needs to know, reason, act, remember, and learn. That architecture powers three products:
- Graphon Enterprise: secure, governed memory across enterprise data across all modalities, so agents and teams can search and reason over it, deployed on hosted, Graphon-managed VPC, customer-managed VPC or on-prem infrastructure
- Graphon Developer: builders can build over any data or modality without recreating the context stack
- Graphon On-Device Memory: private, persistent multimodal intelligence on phones, laptops, cameras, wearables, and other devices
“This funding takes us from early experimentation to scaled enterprise deployments, opens our infrastructure to developers, accelerates our research, and brings Persistent Intelligence on-device,” Khan said. “Those are steps toward a bigger goal. When intelligence becomes lossless and continuous, it compounds, it improves faster, and eventually superintelligence becomes available to everyone. We’ll measure our success by whether we build the infrastructure that gets intelligence to its next stage and make it available to all.”
About Graphon Labs
Graphon Labs is an applied AI lab building Persistent Intelligence to power the next generation of AI agents and accelerate progress toward AGI. Persistent Intelligence enables AI to continuously access, understand, remember, and build upon everything that came before. Built on graphons, its architecture preserves knowledge, relationships, sources, and time across any type of data. It powers three products: Graphon Enterprise, Graphon Developer, and Graphon On-Device Memory. The company was founded by senior engineers and researchers from Amazon, Meta, Google, Apple, NVIDIA, and other leading research institutions. For more information, visit graphonlabs.com.
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