Latest news with #InitializedCapital
Ya Biladi
6 days ago
- Business
- Ya Biladi
Moroccan entrepreneur raises 4.2 million for AI startup ZeroEntropy
US-based Moroccan entrepreneur Ghita Houir Alami, co-founder and CEO of the AI startup ZeroEntropy, has raised $4.2 million in a seed round led by American venture capital firm Initialized Capital. ZeroEntropy (YC W25) builds high-accuracy search systems for retrieval-augmented generation (RAG) and AI agents. Since its launch in January, the company has processed nearly 100 million documents and close to one million queries. The company also announced the release of its state-of-the-art reranker, zerank-1, a new AI model that significantly improves search accuracy. It enhances any first-stage search system, including BM25 and OpenAI embeddings, by up to 28%, and outperforms top models like Cohere's rerank-3.5 and Salesforce's LlamaRank in domains such as finance and STEM, reads an introduction by the company. «The newly launched zerank-1 model, trained using a chess ELO score-inspired pipeline, outperforms every other model on public and private benchmarks while being faster and cheaper», Ghita said in a video shared last week on her social media. «And here's the best part: zerank-1 is already live through our API and fully integrated into our search engine. So if you are using ZeroEntropy, your retrieval just improved automatically». Originally from Rabat, Ghita holds a master's degree in Applied Mathematics from UC Berkeley, with a focus on Machine Learning and Operations Research. She also earned a BS/MS in Applied Mathematics from École Polytechnique, France's top engineering school, where she specialized in Data Science. Her academic journey began at the elite preparatory program of Lycée Sainte-Geneviève, and she graduated with highest honors from Lycée Descartes in Rabat. Ghita was also a top 10 finalist in the U.S. Embassy's science contest and received an Honorable Mention at the 2017 International Physics Olympiad.
Arabian Post
10-07-2025
- Business
- Arabian Post
Moroccan‐Born Duo Secures $4.2 Million to Sharpen AI Search Precision
San Francisco–based ZeroEntropy has emerged at the forefront of a crucial yet underrepresented segment in artificial intelligence: retrieval‑augmented generation. The startup, co‑founded by Moroccan engineer Ghita Houir Alami and CTO Nicolas Pipitone, has raised $4.2 million in seed funding to refine how large language models access contextually relevant data. This investment underscores growing investor conviction that LLM performance hinges on the quality of retrieved information, not just model size. ZeroEntropy's funding round was driven by Initialized Capital, with contributions from Y Combinator, Transpose Platform, 22 Ventures, and a16z Scout. Angel support included operators from leading AI platforms such as OpenAI, Hugging Face, and Front. Initialized partner Zoe Perret highlighted the startup's standout offering: 'Retrieval is undeniably a critical unlock in the next frontier of AI, and ZeroEntropy is building it'. Key to ZeroEntropy's solution is its API, which streamlines the ingestion, indexing, embedding, re‑ranking, and evaluation of data sources—a departure from the piecemeal approaches typical in the field. Its proprietary re‑ranker, ze‑rank‑1, claims superior performance on public and private benchmarks, outperforming models from Cohere and Salesforce. The startup emphasises that effective retrieval must go beyond semantic similarity; it must interpret nuanced queries involving negation, multi‑hop reasoning, and fuzzy filters—capabilities that standard systems often miss. ADVERTISEMENT Developers using ZeroEntropy gain a 'Supabase for search' experience, according to Houir Alami, enabling rapid deployment of high‑precision retrieval systems even across messy internal documentation. More than ten early‑stage AI startups spanning healthcare, legal, customer support and sales are among its initial adopters. Houir Alami's background is integral to the company's vision. Raised in Morocco, she earned engineering credentials at École Polytechnique in France before pursuing a master's in mathematics at UC Berkeley. Her experience attempting to build a conversational AI prior to ChatGPT's rise clarified the importance of structured, precise context retrieval—a realisation that shaped ZeroEntropy's mission. At 25, she is a rare female leader in AI infrastructure, and her outreach efforts in Morocco aim to inspire more young women to pursue STEM fields. The funding will be used to expand engineering and go‑to‑market capabilities. As AI systems become more integrated into workflows, LLM hallucinations—errors resulting from irrelevant or inaccurate retrieved context—pose growing risks in mission‑critical domains. Legal reasoning, medical decision‑making, and financial analysis demand systems that can reliably source authoritative evidence. ZeroEntropy's platform seeks to ensure that AI agents not only surface relevant data but contextualise and rank it properly, reducing risky missteps. RAG architecture remains the go‑to method for generative AI tools—chatbots referencing HR policies or legal documents, customer‑support agents pulling from product manuals—but its effectiveness depends on retrieval robustness. Competitors like MongoDB's VoyageAI and fellow YC startups such as Sid. ai target similar spaces. Yet ZeroEntropy's focus on a unified API and superior re‑ranking appears to distinguish it. Investor and market perspectives affirm the strategic significance of RAG. Initialized Capital's support, along with angel participants from well‑known AI firms, signals institutional belief in ZeroEntropy's potential to become foundational infrastructure for developers building LLM‑enhanced applications. The round's breadth—spanning VCs, angels, and YC—reflects confidence across the investment community. ZeroEntropy's approach is particularly relevant as AI adoption scales in domains requiring stringent compliance, audit trails, and domain specificity. In such environments, AI agents must offer traceable citations and verifiable output. ZeroEntropy's API gives teams a deterministic retrieval backbone, improving both speed and reliability of source retrieval. Ze‑rank‑1's benchmark performance provides early validation for its technological edge. The company's trajectory—from its founding in 2024 to securing major investment in mid‑2025—reveals rapid market resonance. The startup's diaspora roots, bridging Morocco, Europe and Silicon Valley, also reflect AI's increasingly global talent landscape.
Business Wire
06-05-2025
- Business
- Business Wire
Trilobio Raises $8M to Deliver Whole Lab Automation for Biologists
SAN FRANCISCO--(BUSINESS WIRE)-- Trilobio, the Company building the fully automated robotic lab-in-a-box for biologists, today announced it has raised $8 million USD Seed investment. The oversubscribed round was led by Initialized Capital, including participation from Argon Ventures and Lowercarbon Capital. Trilobio was founded in 2021 to address the established data quality and reproducibility challenges limiting research efficiency; it is estimated that 77% of biologists cannot reproduce their own or other's research, despite latest advances in laboratory automation tools (1). Trilobio's co-founders, Roya Amini-Naieni and Maximilian Schommer, were named on Forbes' 30 Under 30 list for their contributions to advances in Manufacturing & Industry. To date, the Company has raised over $11 million, including support from Julian Capital, Juniper, Future Labs Capital, 1517 Fund, Alumni Ventures, Angel Squad, Sequel, Nucleus Capital, Gaingels and others, and has deployed its whole laboratory automation platform at leading biology labs across the United States. This investment will support the expansion of the Trilobio Platform's robotics capabilities and no-code software features, enabling a growing portfolio of purpose-built lab devices and protocols to be integrated into a single, fully automated platform. Leveraging continual advancement and expansion of the Platform, Trilobio is providing an accessible and scalable solution to transform genetic engineering, synthetic biology and life science research processes, enabling scientists at the cutting-edge to execute research reproducibly, rapidly, and accurately. Roya Amini-Naieni, CEO and Co-Founder at Trilobio, commented: 'Today's research is more collaborative, innovative, and insightful than ever before, and yet has not reached its full potential because of our inability to reliably reproduce, share, and collectively improve experiments. The future of the field depends on affordable new technologies that empower scientists to overcome these obstacles. ' She added: 'Our mission at Trilobio is to redefine the relationship between scientists and the technologies that power their work every single day, enabling new scientific heights to be reached. We are thankful to have the support of a fantastic portfolio of investors who share our vision. It's time for true automation–connecting and fully automating all processes in the modern biology lab and making the dream of walk-away capabilities a reality.' The Trilobio Platform consists of the foundational robot, the Trilobot, which is fully programmable through Trilobio OS, the intelligent no-code protocol design software. Each Trilobot houses up to eight different interchangeable lab device tools, effectively creating a self-contained lab in a single device, for example grippers, various pipette tools, and a tube cap/de-capper. The Trilobots, which automatically calibrate themselves and plasticware, can be instantly linked together and work collaboratively, enabling a fleet to be adjusted to individual research requirements and scale capacity instantly. A user's research protocol is entered into Trilobio OS just like writing a lab notebook entry, initiating the software engine to plan and execute all details without further action required and eliminating hours of coding and research design. Trilobio OS determines the optimal execution of the protocol which can be automatically adjusted for speed, cost, or accuracy. In total, the Trilobio Platform is purpose-built to ensure each step of the workflow is reproducible in any other Trilobio-enabled lab, without the need for hardware recalibration or rewrite of protocols. By providing a reliable and standardized approach, the technology streamlines research design and execution time down to minutes from days or even weeks. 'Roya and Max are uniquely qualified to build the future of lab automation given their interdisciplinary expertise in biology and robotics. I've never seen another founding team with this skillset," said Andrew Sather, Partner at Initialized Capital. "Trilobio is a force-multiplier for the Bio Age, empowering scientists to improve our quality of life and move our species forward." For more information about Trilobio's platform, please visit:
