Generative AI as a Service
Customizable, Ready-to-Launch Generative AI Solutions to Kickstart Your AI-Powered Solution
Activate Your GenAI Solution in 8 Weeks or Less
Leverage advanced AI capabilities without the need of technical expertise or resources to develop your own AI/LLM models yourself. Take advantage of Sphere’s pre-made, highly customizable solutions and use-cases to launch your customized solution in as little as two months.
Integrated GenAI Solution
Fast Implementation In < 8 Weeks
Leverages Smart Language Learning Models
Powering the World’s Leading Businesses
Ready-to-Go GenAI Solutions for Any Industry
Get your AI-powered application ready to go in 8 weeks or less. Our customizable GenAI solutions are pre-built with database connectors and common software integrators—designed to quickly sync with your current tech stack environment. Our engineers then further refine these solutions based on your specifications such as security prerequisites, industry compliance standards and other requirements.
Knowledge Extraction Engine
PRIMARY USE-CASE
Automated text/information extraction (PDFs, Word Docs, etc.). Endpoint-based integration for application/workflow logic.
CLIENT REQUIREMENTS
- List of formats of planned documents & images to process
- Small sample size of documents to ensure accuracy of the solution
TIMELINE
~6 weeks to build + post-build testing
Chatbot-Powered Support
PRIMARY USE-CASE
Customer service or internal assistant support chat interface. This chatbot typically features real-time information retrieval from any database.
CLIENT REQUIREMENTS
- Structured data source + integration end point(s)
- Data schema definitions
TIMELINE
~6 weeks to build + post-build testing
Rich Media-to-Text Summarization
PRIMARY USE-CASE
Text and information extraction from images and videos. Samples include image captions, video subtitles and more.
CLIENT REQUIREMENTS
- Image and video samples
TIMELINE
~8 weeks to build + post-build testing
Personalized Content Generation
PRIMARY USE-CASE
Persona-based user segmentation—automatically generating matching images and text based on the parameters for each persona.
CLIENT REQUIREMENTS
- User data for various segments
- Base text/image templates
- Sample content to personalize
- Brand/company guidelines to follow
TIMELINE
~8 weeks to build + post-build testing
Synthetic Data Generation (Model Training)
PRIMARY USE-CASE
Generate quality data based on a limited historical data set; commonly utilized for building a training pipeline for AI model training and accuracy improvement.
CLIENT REQUIREMENTS
- Clean/structured historical data
- Parameters for data generation
TIMELINE
~8 weeks to build + post-build testing
Sentiment Analysis
PRIMARY USE-CASE
Data-based sentiment extraction & analysis. Commonly used to determine a writer’s (of any body of text) attitude towards any particular topic, or creating a sentiment-powered workflow/logic.
CLIENT REQUIREMENTS
- Input data source (structured or unstructured)
TIMELINE
~6 weeks to build + post-build testing
Data Analytics and Summarization
PRIMARY USE-CASE
Data integration; real-time summarization and analysis of any data set
CLIENT REQUIREMENTS
- Structured data set
- End point for data consumption
TIMELINE
~8 weeks to build + post-build testing
Custom Solution
Don’t see your use-case listed? Not sure exactly where to start?
We have more pre-built, customizable solutions that we can easily adapt and modify to your specifications. Contact us below, and let’s talk!
GenAI Application Use-Case Leaderboard
Sphere’s prebuilt, customizable GenAI solutions can be immediately applied to any industry, business and internal/external operations. Learn more about some of the leading use-cases our clients have implemented onto their company—creating significant positive impact.
Dynamic Content Generation
Image/text-based marketing collateral generation within seconds. Generated based on pre-loaded personas and segments.
Product Description and Pricing
Automated product listing and real-time product pricing recommendations based on customer behavior data and/or market competitor data.
Claims Settlement
Customer support automation for semi-complex transactions. Leverages LLaMA2 to automate policy document data extraction and execution of settlement workflow.
Corporate Regulatory Compliance Management
Automated regulatory management for corporate due diligence. Reads and extracts from documents and processes to enact workflows across departments.
Code Generator LLM
Get instant, 100% clean code based on personalized insights on your data input. Instantly generate code in Python, Ruby and others.
Data Query and Analytics
Immediately receive valuable information based on natural language queries in a chatbot-style interface. Enable your analytics team with real-time analysis of large data sets.
Why Sphere?
Generative AI Case Studies
Find out more
AI Partnerships
We will help you get the right AI tech, for the right purpose, to build the right architecture so you can transform your business. We have experience with all modern data, AI and analytics tools and will make sure you’re taking full advantage of the benefits available across your entire data stack.
GenAI: Did You Know?
According to a Gartner study, only 9% of organizations have a concrete AI vision in place. Furthermore, over a third (36%) have no plans whatsoever to develop one.
Companies that do not have an AI strategy will consequently fall behind in speed, efficiency and innovation, and are missing out on the biggest technology disruptor of the decade.
In the succinct words of Gartner, “If you don’t have an AI vision, you don’t have an AI ambition.”
Answering “Are You AI-Ready?” With Sphere’s GenAI Readiness Program
According to a study by Google, in 2022, most people are currently AI Explorers: companies with “varying degrees of data readiness to harness the power of AI and machine learning.” AI Explorers may have heard of AI, but typically do not have a strong idea of how to start taking advantage of the technology, unsure of how much resources to allocate or how long such a process would take.
Enter Sphere’s GenAI Readiness Program.
Sphere’s GenAI Readiness program has been meticulously designed as a quick-start launchpad towards immediate GenAI implementation. Through this program, you can expect the following key results to give you the insight and plan that you need to enable GenAI for your company—within just a few quick sessions with your team.
- Education Deck: An in-depth compilation encapsulating the vital facets of GenAI, paving the way for informed decision-making and strategic alignment.
- Executive Report: A concise distillation of key takeaways, challenges, and opportunities, crafted to give C-level leaders a clear picture of the GenAI landscape and its implications for their org.
- Strategic Roadmap: A custom-designed roadmap delineating integration points, potential projects, and a tactical strategy for POC execution, tailored to maximize ROI and ensure organizational alignment.
- Informed Insights: A meticulous breakdown of our findings, from the Goal Review & Technical Deep Dive to the IP Feasibility Study, offering a granular view of your organization’s GenAI readiness and potential.
Featured Team Members
Leon Ginsburg
Founder and CEO
A digital innovations leader, technologist, investor, and entrepreneur, Leon founded Sphere Software in 2005 to revolutionize the delivery of remote teams. He has a passion for people, products, processes, and technologies that not only perform well, but also are human-centric and meet the needs of the user.
Boris Korenfeld
Global CTO & General Manager of Tech Practices
Boris has held various roles since 2000 and worked for several of the world's leading organizations, including HP Software, Gett Taxi, and Google. He helped build a variety of products in different domains and led high scale tech teams to success. He is passionate about leadership, change management and innovation; using his experience in these areas to make an impact to global businesses.
Igor Meltser
VP of Global Technology Solutions and Services
Igor has extensive technical and operational experience, spending the last 15 years of his career in various Healthcare-related IT roles. With almost 20 years overall in small entrepreneurial and large global tech-forward organizations, Igor leads cross-functional teams to design and deliver innovative high-tech solutions to aid in the continuum of care. He holds a Master’s Degree in Information Systems Technology, Networking and Security, and two Bachelor degrees in Computer Science and Information Systems from DePaul University. Igor previously held a CCNA certification and had successfully completed a SAFe Foundations bootcamp program.