OPSMO - Machine Learning Driven Business Support Tool for Tech Startups

OPSMO - 面向科技初创企业的机器学习驱动的业务支持工具

• 批准号: 10035790
• 金额: $ 30.47万
• 依托单位: OPSMORPH LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10035790
• 关键词: OPSMO; Machine; Learning; Driven; Business

For tech consultancies and startups, searching advertised contract opportunities, be it a project in the public sector or an individual consultant contract, is time consuming and costly. Writing a bid can take one or two months and a fulltime bid coordinator can cost upwards of £30k/year. Proposal success rates are typically 1 in 12 meaning a tech startup may be without funding for an entire year, which for early-stage startups can be fatal. Technology is changing rapidly and staying informed of cutting-edge developments across every layer of the software stack, across every algorithmic technique, and across every cloud provider is almost impossible, which inhibits CTOs and CEOs from making strategic investments in skills and services. Existing small consultancies of various expertise aiming to pivot towards tech to take advantage of the substantial opportunities find it challenging to upskill their knowledge of tech quickly enough to generate winning ideas and the time of their often-limited technical resources can be hard to obtain. A step change solution is needed to convert creative innovation into sustainable growth.OPSMO uses machine learning and graph database technology to deliver a technical bid writing support system for tech startups that identifies funding opportunities, inspires ideation and innovation, and informs cost and risk estimates. It streamlines proposal writing, reducing writing time and bid writing resource costs. By capturing galaxies of data on cutting edge technological innovations, OPSMO associates tech stacks with problems, paints a picture of the solution, and generates the required team roles, associated costs and risks associated with the stack. By fast tracking bid writing, OPSMO liberates startups to network, brainstorm, create, iterate, and build.Through its fully automated data ingestion pipeline, OPSMO streams data on contract opportunities in the UK and Europe; data on tech jobs, roles, skills, and salaries; data on technological innovations, their uptake trends, and the connections between them; and builds a big data knowledge graph to associate technological advances with funding opportunities and problem spaces. Recent developments in deep learning natural language processing provide OPSMO's algorithms with enhanced capabilities for extracting mentions of technological tools from text, for classifying funding opportunities by theme, for calculating association strengths between tools, and to track trends in the popularity of solution architecture. OPSMO's cloud hosted graph database provides 100,000 queries per second across billions of connections giving startups a smooth user experience when accessing its targeted knowledge graph, unmatched in scale an insight.

对于科技咨询公司和初创公司来说，搜索广告中的合同机会，无论是公共部门的项目还是个人顾问合同，都是耗时和昂贵的。写一份标书可能需要一到两个月的时间，一名全职竞标协调员的费用可能高达3万GB/年。提案成功率通常为12%，这意味着一家科技初创公司可能一整年都没有资金，这对处于早期阶段的初创公司来说可能是致命的。技术日新月异，几乎不可能在软件堆栈的每一层、每种算法技术和每一家云提供商之间随时了解尖端发展，这阻碍了首席技术官和首席执行官在技能和服务方面进行战略投资。现有的小型咨询公司拥有各种专业知识，旨在转向技术领域，以利用大量机会，但它们发现，要迅速提高自己的技术知识，以产生制胜的想法，是一件具有挑战性的事情，而且他们往往有限的技术资源的时间可能很难获得。OPSMO使用机器学习和图形数据库技术，为科技初创企业提供一个技术标书撰写支持系统，该系统能够识别融资机会，激发想法和创新，并告知成本和风险估计。它简化了提案撰写，减少了撰写时间和投标撰写资源成本。通过捕获有关尖端技术创新的大量数据，OPSMO将技术堆栈与问题联系起来，描绘出解决方案的图景，并生成所需的团队角色、相关成本和与堆栈相关的风险。通过快速跟踪投标，OPSMO将初创企业解放出来，让它们建立网络、集思广益、创造、迭代和建立。通过其全自动数据接收管道，OPSMO传输有关英国和欧洲合同机会的数据；关于技术工作、角色、技能和工资的数据；关于技术创新、其采用趋势以及它们之间的联系的数据；并构建大数据知识图谱，将技术进步与融资机会和问题空间相关联。深度学习自然语言处理的最新发展为OPSMO的算法提供了增强的能力，用于从文本中提取对技术工具的提及，用于按主题对资助机会进行分类，用于计算工具之间的关联强度，以及跟踪解决方案体系结构的流行趋势。OPSMO的云托管图形数据库每秒提供10万次查询，跨越数十亿个连接，使初创企业在访问其目标知识图谱时获得流畅的用户体验，在规模和洞察力方面无与伦比。