Microsoft Personal Capital and International Impartial Software program Vendor Groups, in collaboration with Madrona Ventures, just lately organized a GenAI hackathon for portfolio corporations, hosted on the Redmond campus. 33 members from Amperity, Clari, Highspot, and SeekOut, shaped seven groups, to discover generative AI options. Previous to the Hackathon, members crafted distinctive drawback statements and strategized with Microsoft coaches on the way to leverage Generative AI’s potential to handle enterprise or finish buyer challenges, improve product options, or propel product/function growth. The aim was to finish the two-day hackathon with proof of ideas, AI-enabled, and a path ahead to take these options to manufacturing.
The groups have been judged throughout three key themes: 1) the use case and innovation, 2) inserting people on the core with a deal with the answer’s worth to people, and three) the incorporation of Accountable AI practices.
Let’s see what they got here up with:
Amperity
Amperity, a Buyer Knowledge Platform, empowers manufacturers to develop by gaining a deep understanding of their clients. It offers an information basis for buyer acquisition, retention, customized experiences, and privateness administration.
The Amperity workforce determined to leverage AI to make it simpler for advertising and marketing management and no-code enterprise resolution makers to work together with information from disparate, unstructured information unfold throughout emails, social media, and transactions, to raised plan and serve their clients.
The challenge centered on utilizing GPT-4 by means of Azure Open AI Service to develop a conversational assistant to research buyer information and allow all workforce members to make data-driven selections. They remodeled conversations on to SQL queries executed towards buyer profiles databases and displayed in tables. This course of simplifies information interpretation, making it accessible to all workers.
Amperity then used OpenAI’s code interpreter to Generate graphical representations.
The result’s a unified, 360-degree view of a buyer that was beforehand scattered throughout a number of touchpoints. This holistic perspective permits entrepreneurs, buyer expertise groups, and decision-makers to know their clients on a deeper stage.
One other means Amperity creatively used AI is showcased by means of icons from question outcomes:
The crown icon is chosen by the AI mannequin primarily based on the generated output “PLATINUM_CUSTOMERS”.
The format, icons, and general presentation can now be dynamically generated. This multifaceted strategy, the place the aspect is chosen by AI, represents a brand new period in UI design, opening a world of potentialities for startups to create extra adaptive and user-friendly interfaces.
A serious spotlight of the challenge addressed potential points with SQL by passing any SQL errors again to GPT for auto-correction. This saved time and improved the system’s effectivity and reliability. Amplified demonstrated a stage of automated problem-solving, which is a game-changer for startups trying to develop rapidly.
Highspot
Highspot is a gross sales enablement platform that equips gross sales groups with the instruments, content material, and insights wanted to enhance efficiency and drive income.
They offered three approaches to rising gross sales productiveness by means of AI.
Highspot Staff 1
Showcased their progressive use of AI to enhance person expertise and enhance productiveness.
Highspot Staff 1 targeted on three major themes: automation recommendation, co-creation, and a function they’re tentatively calling, “Ask Something”. The corporate has carried out AI in its product to generate descriptions for content material, create assembly summaries, and compose messages, amongst different options.
‘Ask Something’ surfaces paperwork and content material primarily based on questions posed by the person. This function could possibly be particularly helpful for customers in enablement and advertising and marketing to generate descriptions for content material.
They demonstrated that whereas looking for a doc they will present solutions to a person’s particular questions concerning the doc itself. They even automated follow-ups, the place the system can ship follow-up emails that embody particular particulars mentioned within the rep’s buyer assembly.
Highspot is engaged on integrating these functionalities into their extensions for Slack and Microsoft Groups. This may allow customers to ask questions inside these shoppers and obtain direct solutions concerning the product or some other associated question.
Their implementation works significantly nicely for giant paperwork the place the search can recall particulars deep inside the textual content.
For recordings in Microsoft Groups Highspot can ask, “What did they speak about once they talked about matter X?” or “What did particular person XYZ say a couple of sure matter?”
In essence, making it simpler for gross sales groups to entry vital data rapidly.
The Highspot workforce utilized gpt-35-turbo-16k from OpenAI, mixed with Microsoft applied sciences, to boost their pure language understanding and technology capabilities. Utilizing Azure OpenAI’s sturdy infrastructure and complete toolset enabled Highspot to develop, check, and deploy their AI options swiftly and effectively.
The important thing constructing blocks of Highspot’s structure embody OpenAI Perform routing for question classification and information binding, and dynamic UI rendering primarily based on question intent. These parts work in tandem to create a seamless person expertise, the place the system can perceive person queries, classify them, and render acceptable responses dynamically.
Highspot Staff 2
Highspot Staff 2 targeted their efforts on integrating gross sales enablement capabilities extending Copilot for Gross sales. The challenge goals to boost the productiveness of gross sales groups by streamlining entry to related information, decreasing the necessity for context switching between totally different instruments and by offering related insights and automating duties all inside Outlook.
The context {that a} vendor must reply an e-mail is pulled from the Highspot’s platform into Copilot. This consists of views, downloads, recipients from Highspot in addition to CRM information from Salesforce.
Leveraging Salesforce information permits the Copilot to supply predictive content material suggestions. By analyzing the CRM information, Highspot can establish tendencies and patterns in buyer conduct and supply gross sales reps with essentially the most related content material and alternatives for every distinctive buyer interplay.
This permits the sellers to make selections, streamline their workflows, and in the end shut offers sooner.
The workforce utilized Microsoft Copilot for Gross sales with Highspot Connector to create a dynamic Copilot UI that adjusts primarily based on the Highspot context. This integration allowed for a seamless transition between Highspot and Copilot, enhancing the person expertise and boosting productiveness.
Highspot Staff 3
Highspot Staff 3 targeted on teaching gross sales representatives and showcased why it’s so important for sellers. Drawing from educational analysis, they highlighted the numerous enchancment in efficiency when college students obtain one-on-one mentorship or teaching. In a company context, the identical precept applies. In reality, gross sales reps who obtain two hours or extra of teaching per week have 56% or greater win charges.
Teaching usually falls by the wayside in lots of organizations as a result of time constraints and a scarcity of formalized teaching strategies. Staff 2 aimed to offer gross sales reps suggestions on their abilities demonstrated in real-world conferences and help managers in offering customized teaching.
To realize this, they utilized Microsoft Groups’ transcription and recording API, together with rubrics, query context, reply guides from Highspot, and Azure’s OpenAI GPT-3.5 Turbo mannequin. They staged a gross sales discovery name between Contoso (the vendor) and Fabrikam (the prospect) and used GPT to create a transcript. This supplied the idea for his or her suggestions system.
Gross sales reps submit a recorded assembly for suggestions. The suggestions relies on predefined rubrics and offers detailed insights into their efficiency. Gross sales reps can then submit their conferences, together with the AI-Generated suggestions, to their managers for additional evaluate. Managers even have the choice to Generate AI-assisted suggestions, which they will then personalize earlier than submitting it to the rep.
The principle constructing blocks of their structure included a React entrance finish, Highspot’s assembly ingestion leveraging MS Groups APIs, and Azure OpenAI APIs. Nevertheless, the implementation was not with out its challenges. Figuring out the assessed topic within the immediate proved tough, necessitating numerous methods to research the transcription to make it useful.
SeekOut
SeekOut is a people-first, AI-assisted expertise acquisition and administration platform that gives complete information, uncovers unnoticed candidates, and helps worker development.
SeekOutTeam 1
SeekOut Staff 1 showcased a prevalent problem within the job market – private profession teaching. The workforce highlighted the inequitable distribution of profession teaching providers and the prohibitive prices related to them.
Their answer? “Yoda,” an AI-driven profession coach, set to democratize profession teaching by making it accessible to everybody.
Profession teaching is commonly out of attain for many workers as a result of its excessive value. Human coaches require an intensive understanding of their shopper or mentee’s background, pursuits, values, and profession aspirations, which regularly requires a big quantity of effort and time. Yoda, makes use of generative AI to know a person’s background, abilities, pursuits, and targets, offering customized suggestions.
The AI-driven profession coach, Yoda, was designed to know the nuances of a number of industries, a process that may be difficult for a human. It additionally scales throughout all workers inside a corporation, making it an economical answer for HR groups.
Yoda makes use of Microsoft Groups app and integrates with Profession Compass, which pulls in information from numerous inside and exterior sources to create a complete profile for every person. They used GPT 3.5 turbo to generate and parse the chats, analyze jobs, and profile data to supply customers with personalized suggestions.
It solves two particular use circumstances: 1) customized profession pathing and scanning all the group for brand new alternatives, and a pair of) solutions of inside networking contacts and potential mentors. Yoda considers the person’s profile, transition information, and job positions to recommend potential roles that the person would possibly excel in.
Think about the person persona, Jeanne, a methods engineer trying to transition into software program engineering.
The chatbot integrates with studying methods and inside job boards, offering customers with a wide range of assets to assist their profession development. As well as, it suggests connections inside the group that customers can attain out to for insights and recommendation.
AI drafts introductory messages for customers to ship to potential connections. This function helps customers break the ice and provoke conversations, which may usually be a frightening process.
The workforce didn’t cease at offering suggestions. Yoda constantly scans the group for brand new alternatives that match the person’s profession targets. When an acceptable alternative arises, the chatbot sends a personalised message to the person, summarizing the place and explaining why it is likely to be a very good match.
A person can save their profession selection by means of the chat utilizing pure language, integrating actions along with pure content material technology and suggestion.
The SeekOut Staff 1 believes Yoda provides a novel answer for hyper-personalized profession teaching and scalability. Their presentation included the potential for this instrument to supply high-level insights to HR and organizational leaders, akin to widespread profession progressions, desired abilities, and developmental wants.
They plan to additional combine the Profession Compass app inside groups, gamify abilities growth, and add Yoda to the supervisor’s expertise to assist managers in serving to workers develop and develop.
SeekOutTeam 2
SeekOut Staff 2 showcased a game-changing answer to allow expertise leaders to reply crucial questions like, “What abilities does my group have and the way can I successfully discover folks with these abilities and arrange them higher?” The workforce launched a dynamic abilities platform that leverages Microsoft 365 and OpenAI to supply insights into the skillsets of workers, providing a brand new stage of understanding for expertise leaders.
Understanding Worker Abilities
Staff 2’s answer targeted on serving to organizations perceive the expertise they’ve and the way to develop it. They developed a abilities intelligence platform that ingests information from numerous sources, together with resumes, GitHub, and different skilled paperwork.
The platform makes use of this information to construct relationships between abilities and the way they relate to the bigger organizational image. It additionally offers proof of how totally different workers have demonstrated their abilities.
The dynamic abilities platform seeks to know what the worker has completed and what sort of abilities they’ve demonstrated of their productiveness instruments and resumes. The platform is designed to adapt to real-time context when somebody is utilizing it, permitting for extra particular queries. For instance, as a substitute of asking which individuals have machine studying as a ability, a expertise chief can ask, “How is machine studying utilized by information scientists at my firm?”
The platform’s integration with Microsoft 365 utilizing Microsoft Graph API provides extra depth to the talents platform. It takes paperwork from Microsoft 365, feeds them into Azure OpenAI to generate data on the talents, after which provides this to the talents database. This data is then accessible by means of the Abilities Explorer software.
The workforce demonstrated how a hiring supervisor at Firm X may use the platform to know the talents of a program supervisor. The platform breaks down the talents profile for the function, exhibiting useful, technical, and management abilities. The supervisor can then delve deeper into every ability, seeing proof from resumes, job postings, and Microsoft 365 recordsdata.
The platform additionally offers a means for the supervisor to see how particular abilities, like challenge administration, are utilized by program managers at Firm X. The supervisor can see paperwork linked to the ability and the small print of those paperwork. This data can assist the supervisor perceive what abilities they want for a brand new function or craft a job description for an open place.
Privateness and Subsequent Steps
The SeekOut workforce took privateness into consideration, making certain all information ingestion runs within the buyer’s setting. There’s a layer of information separation to guard person information, and buyer information by no means involves the SeekOut workforce.
Tech stack
The workforce utilized the gpt-3.5-turbo mannequin with Microsoft Graph API, Azure OpenAI, and Azure SQL for his or her dynamic abilities platform. The structure of their answer comprised a number of key constructing blocks. These included the Graph API to obtain workforce content material from Microsoft 365, an offline OpenAI information pipeline to find out the talents demonstrated by the authors of the One Drive paperwork, and a SQL database backend to retailer the connection between abilities and workers.
The workforce’s answer concerned pulling information from Google Drive and embedding it into Azure’s Cognitive Search. This allowed them to course of the info and make it searchable for the engineering workforce.
The workforce showcased their answer by asking it questions on particular incidents or points. The system recognized related paperwork and supplied hyperlinks to the unique runbooks or incident reviews and any technical documentation concerning the instruments they’re utilizing.
The workforce’s challenge was a captivating demonstration of how AI and cloud applied sciences may be leveraged to streamline inside processes and enhance effectivity. They used GPT 3.5 Turbo, obtainable by means of Azure OpenAI Service. The structure was primarily based on an ordinary RAG sample carried out utilizing Azure Cognitive Seek for the Vector Database.
The answer concerned a number of parts, akin to Google Drive integration for doc ingestion, LlamaIndex for doc processing and orchestration, Azure Cognitive Seek for storing embedded chunks, and Streamlit for a easy chat interface.
Regardless of some challenges, they demonstrated how startups can leverage these to boost their inside processes. The workforce’s dedication to enhancing their system, akin to their plans to handle the difficulty with acronyms and codes in semantic search and to assemble person suggestions, underscores the continual evolution and potential of AI options within the enterprise world.
And the winner was….
Highspot Staff 2! Highspot Staff 2’s answer not solely aligned with the hackathon’s targets but in addition demonstrated a sensible and impactful strategy. Consequently, the work of their larger workforce was included in Satya Nadella’s keynote presentation at Microsoft Ignite.
To our winners, you’ve rocked this along with your unbelievable abilities and innovation. And to all our members, your power and creativity actually lit up this occasion.
Each one in all you is a star in our tech galaxy. Maintain shining and see you on the subsequent hackathon! 🚀
