We start the project with the initial solution architecture design document which consists of the data processing pipeline, monitoring service & hypotheses, and best fitting Machine Learning / Deep Learning architectures.
Our data science & AI dev team adjusted Agile methodologies from web development for Machine Learning / Deep Learning R&D cycle including Kanban and Scrum.
To set up the R&D process, we configure the tools and team operations to track, control, and iterate on the progress.
Our ML development team assists with anonymizing and depersonalizing any sensitive user data, gathering and labeling custom datasets via data labeling partners or state of the art models, and cleaning the data for further exploratory data analysis. Once the data is ready, we develop the Machine Learning / Deep Learning Pipeline. We launch training and parameters tuning cycle, then test the model in inference mode and optimize graphs to achieve defined metrics in terms of accuracy & speed.
In parallel with Model Development and Training, we launch the service development process where we merge the entire data pipeline with the Machine Learning / Deep Learning Pipeline. After that, we develop the end API, service, or package which will be used in production. We deploy the solution to any required destination such as cloud, dedicated servers, mobile, or embedded devices.
By integrating monitoring, performance testing, and CI / CD systems, we gather insights on new data, data anomalies, and key metrics that serve as a trigger to continue improving model performance. Once the service is up and running, we document the full solution and train the client’s team to use it correctly by conducting knowledge transfer workshops. When necessary, we develop new features, improve the performance, keep the accuracy high and support the project on the ongoing basis.
We start the project with the initial solution architecture design document which consists of the data processing pipeline, monitoring service & hypotheses, and best fitting Machine Learning / Deep Learning architectures.
Our data science & AI dev team adjusted Agile methodologies from web development for Machine Learning / Deep Learning R&D cycle including Kanban and Scrum.
To set up the R&D process, we configure the tools and team operations to track, control, and iterate on the progress.
Our ML development team assists with anonymizing and depersonalizing any sensitive user data, gathering and labeling custom datasets via data labeling partners or state of the art models, and cleaning the data for further exploratory data analysis. Once the data is ready, we develop the Machine Learning / Deep Learning Pipeline. We launch training and parameters tuning cycle, then test the model in inference mode and optimize graphs to achieve defined metrics in terms of accuracy & speed.
In parallel with Model Development and Training, we launch the service development process where we merge the entire data pipeline with the Machine Learning / Deep Learning Pipeline. After that, we develop the end API, service, or package which will be used in production. We deploy the solution to any required destination such as cloud, dedicated servers, mobile, or embedded devices.
By integrating monitoring, performance testing, and CI / CD systems, we gather insights on new data, data anomalies, and key metrics that serve as a trigger to continue improving model performance. Once the service is up and running, we document the full solution and train the client’s team to use it correctly by conducting knowledge transfer workshops. When necessary, we develop new features, improve the performance, keep the accuracy high and support the project on the ongoing basis.
Starting with hiring the anchoring technical leader and by leveraging our technical team’s expertise, we launch the recruitment process for the rest of the tech team. We don’t stop until the last teammate needed comes on board.
When in need of advanced technical expertise, you can leverage our senior AI tech team on demand for AI architecture consulting, Data Science technology stack choice, ML model development training, and other AI-related questions.
We set up the legal entity and infrastructure connecting your main entity with your new employees in the R&D office while protecting your intellectual property. We take care of payroll, taxes, and expense tracking so that you don’t have to.
You can rest assured that we take care of your employees. From regular review sessions and work satisfaction surveys to resolving routine challenges - our HR team keeps the finger on the pulse of your team.
Starting with hiring the anchoring technical leader and by leveraging our technical team’s expertise, we launch the recruitment process for the rest of the tech team. We don’t stop until the last teammate needed comes on board.
When in need of advanced technical expertise, you can leverage our senior AI tech team on demand for AI architecture consulting, Data Science technology stack choice, ML model development training, and other AI-related questions.
We set up the legal entity and infrastructure connecting your main entity with your new employees in the R&D office while protecting your intellectual property. We take care of payroll, taxes, and expense tracking so that you don’t have to.
You can rest assured that we take care of your employees. From regular review sessions and work satisfaction surveys to resolving routine challenges - our HR team keeps the finger on the pulse of your team.
We conduct a free consulting session to understand your startup’s idea, stage, and fundraising needs. We discuss and estimate the services needed, timeline, deadlines, and expectations from our cooperation.
By deep-diving into the startup’s domain, we perform the initial analysis of the market, its incumbent, and emerging players to develop unique company positioning and a profound understanding of its USP, core competitive advantages, and business strategy.
Our Venture Services team prepares essential fundraising documents such as a short and long investment deck, 1-page executive summary to position the company for a successful fundraising campaign. We also assist with the financial model development to support the startup’s growth plans.
By leveraging our investor network and database, we form a long list of investors for initial outreach. Our team assists with scheduling calls and meetings with likely backers, founders pitch, and keeping track of the fundraising funnel.
We conduct a free consulting session to understand your startup’s idea, stage, and fundraising needs. We discuss and estimate the services needed, timeline, deadlines, and expectations from our cooperation.
By deep-diving into the startup’s domain, we perform the initial analysis of the market, its incumbent, and emerging players to develop unique company positioning and a profound understanding of its USP, core competitive advantages, and business strategy.
Our Venture Services team prepares essential fundraising documents such as a short and long investment deck, 1-page executive summary to position the company for a successful fundraising campaign. We also assist with the financial model development to support the startup’s growth plans.
By leveraging our investor network and database, we form a long list of investors for initial outreach. Our team assists with scheduling calls and meetings with likely backers, founders pitch, and keeping track of the fundraising funnel.
Hop on a call with our senior tech team. During one-hour call, get recommendations on development strategy, architecture options, and best AI stack for your solution. Ask away any questions. It is on us.
Detailed AI Solution Roadmap
DataRoot Labs’ AI & ML consulting firm delivers a comprehensive estimate that includes not only transparent pricing but also provides a detailed roadmap with a breakdown of stages, delivery timeline, and team necessary to complete your solution.
Fast MVP Delivery
We move fast to understand your end-product and set up the right team for you. We leverage our recruiting services as well as our proprietary Data Science School to complement our core R&D team with knowledgable experts when necessary. On average, we are able to deliver ready MVP in 8-12 weeks.
Flexible Pricing
We are in it for the long-run. By building lasting relationship with our clients, we provide flexible pricing that meet your budget constrains at the initial stage of AI & ML MVP development. If you are at the idea stage, we can integrate you with our proprietary Data Science School where you can leverage our students to iterate on your product ideas.
Full IP Transfer & Confidentiality
We know how to work with sensitive data and have the tools and processes in place to protect it. Upon project completion, we fully transfer all IP to you. We respect your confidentiality and can keep all development in stealth mode.
Fundraising Support
While you stay focused on product, our Venture Services team assists you with preparing documentation for fundraising including a pitch deck and financial model. By leveraging our network, we form a long-list of investors, perform initial outreach and assist with round closing.
DataRoot Labs delivered a prediction algorithm that achieved a 90% precision rate during tests with synthetic data. Informed by notable industry expertise, the team effectively guides the engagement.
Since implementation, conversion rates have increased. DataRoot was responsive, passionate, and possessed the skills required to make the project a success.
DRL has the professional skills in Deep Learning to successfully research and architecture AI models, train and tune them, and construct the cloud native infrastructure to productize them as a service for us. A pleasure to work with: very insightful, diligent and able to deliver!
Joshua Reuben
AI System Architect and Dev Team Leader @ Kami Computing
