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Floworks Launches New Tool Use Feature in Alisha 3
The new feature allows users to deploy custom workflows in the AI SDR agent, using plain English. YC-backed Indian startup Floworks launched a new feature called 'Tool Use' inside their AI sales development representative, named Alisha. The feature lets customers build custom workflows inside Alisha using natural language and allows users to 'fetch data from and put actions across major sales tools.' Sudipta Biswas, co-founder and alumnus of Indian Institute of Technology Kharagpur, announced the new feature via a demo on LinkedIn. In the video, Biswas demonstrated creating a workflow, which logs a summary of every email under the relevant CRM contact. He also mentioned other workflows created by their clients, which involved looking up a sales document to answer emails, sending meeting slots to prospects, and automating follow-up emails. As mentioned, Alisha can also fetch data from various third-party tools, and integrations like Gmail, Salesforce, Hubspot, Biswas mentioned that this feature is in lieu of Flowork's vision of strengthening the outreach layer by amplifying sustained engagement with prospects through personalised emails and communication layers. We at AIM reached out to Biswas after the announcement. He said that over 50+ Floworks customers have realised the need for workflows based on their organisation's goals and other specifics, and it is 'hard to use a single unified product' - which was one of the main goals of the Tool Use feature. That said, Floworks will also have to battle it out from competing products like Einstein Agent from Salesforce, and Microsoft Copilot - but these platforms only let you integrate tools within the first-party ecosystem from their parent company. While other products like Creatio and DryMerge allow creating automation with plain English while fetching data from more sources and integrations, Biswas believes the fact that Alisha is working on their in-house AI architecture and not relying on an API will play to their advantage. As claimed in their recent research paper for their V2 architecture, Biswas said it has the lowest latency and highest accuracy in fetching data from other tools. "New APIs may require newer development efforts as old prompts may not work, which is a whole new building exercise", said Biswas referring to the difficulty of building over APIs rather than using an in-house architecture. Like Floworks, there are several products, from India, that offer a no-code, or low-code solutions to challenges faces in the enterprise arena. For example, Tablesprint's SaaS platform allows companies to build custom applications for various business functions using open-source and closed-source models available in the market. The startup also raised a $1m seed fund, led by Ola's co-founder Ankit Bhati. In an interaction with AIM, Abhijeet Kumar, CEO at Tablesprint said "We're offering the flexibility of Salesforce but at a Zoho price." "Our focus is on creating a customisable, scalable system that can handle complex enterprise needs without the high costs usually associated with such solutions," he added.
Analytics India Magazine
Mon, 2 Dec, 8:07 AM UTC
Sybill Raises $11 Million for AI-Powered Sales Assistant
Sybill, an AI startup specializing in sales assistance, has secured $11 million in Series A funding. The company's innovative AI technology aims to revolutionize sales workflows by analyzing customer behavior during video calls.
2 Sources
Thu, 1 Aug, 12:01 AM UTC
Sybill raised a $11 million Series A to build an AI assistant for sales reps. Here's an exclusive look at the pitch deck it used.
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Have an account? Log in. Realizing there was nothing in the market, he partnered with Nishit Asnani, Soumyarka Mondal, and Mehak Aggarwal to create a solution, and soon discovered that salespeople shared the same frustrations. "As we started building Sybill, we figured that the use case with sellers, which was to understand buyers' behavior on calls, was coming up the most often," Aggarwal said. In July 2024, Sybill raised a $11 million Series A round led by Greycroft Capital. Other investors include Neotribe Ventures, Powerhouse Ventures, and Uncorrelated Ventures. This latest round brings Sybill's total funding to $14.5 million. Sybill's AI assistant claims to boost B2B salespeople's productivity. Enterprise sales are complex, often spanning several months and involving multiple stakeholders. Thus, sales reps must handle numerous customer requests, frequently switch between tools, and manage internal expectations, said Aggarwal. "They're basically the first soldiers for any organization." Sybill helps sales reps by recording every sales call and generating transcriptions and summaries for future reference. It then analyzes customer interactions across the calls and various tools, including email and Slack, throughout the buyer journey. By consolidating information from these interactions, Sybill helps sales reps gain a clearer understanding of the customers' budget, stakeholders, and timeline. Sybill can also automate many sales workflows, such as updating customer interactions in Salesforce. "Every single sales rep is spending almost three to four hours in their CRM trying to update this information on a weekly basis," said Aggarwal. With Sybill, sales reps can automatically sync information, providing sales leaders with real-time visibility into deals. Additionally, the tool helps salespeople automate emails. With at least five customer calls a week, a sales rep needs to draft emails after each call, which can take up to 25 minutes, said Aggarwal. This manual work can quickly add up. Based on the recorded interactions, Sybill can automatically generate emails with the necessary context and personalization for each customer. Users "trust the system to prepare the right information," Aggarwal said. "We have seen that emails are being sent in the next one to two hours instead of waiting 24 to 48 hours." Other AI sales tools include Gong, an AI-powered revenue intelligence platform that raised $582.9 million, according to PitchBook. The company helps sales leaders forecast revenue and improve team productivity, targeting enterprise customers like ADP and Snowflake. Avoma and WINN.AI are both AI tools that automate sales reps' manual work, while Cresta AI and Balto Software provide AI-driven coaching and call insights for contact centers. Sybill serves over 500 customers, including Ngrok, Supportlogic, and Weaviate. With Sybill, users save more than 2 hours daily on manual work and accelerate deal velocity, said Aggarwal. And this is just the beginning. "Every single rep has 15 to 20 things that they need to do in their week." He plans for Sybill to handle more of these administrative tasks, like customizing sales decks, so salespeople can focus on talking with customers. "Our assistant is geared very much toward helping the salespeople get better at their jobs," said Aggarwal.
Business Insider
Tue, 30 Jul, 4:08 PM UTC
Sybill raises $11M for its AI assistant that helps salespeople reduce administrative burden | TechCrunch
Sybill, a startup that has built an AI assistant specifically for sales representatives, said on Wednesday it has raised $11 million in a Series A round led by Greycroft. The market for sales AI assistants has grown quite crowded as companies have leveraged generative AI and large language models to help salespeople automate grunt work like filling out requests for proposals, updating internal databases and the like. However, Sybill says what sets its assistant apart is its ability to track and analyze many call transcripts and emails, which enables it to provide context-driven insights and summaries instead of only providing meeting notes and transcripts of one or two calls. The startup is also targeting salespeople instead of sales leadership to grow its customer base -- a strategy that has helped it quickly penetrate the market (more on that below). "If the AI output is not accurate, people lose trust in the system very, very quickly," said Gorish Aggarwal, co-founder and CEO of Sybill, in an interview. Sybill says it has built an in-house retrieval-augmented generation (RAG) pipeline on top of existing generative AI GPT models to deliver sales-specific results. The startup analyzes calls, emails and messages between the buyer and the seller using its RAG models to keep additional signals in consideration while delivering output. This deal-level analysis helps limit inaccuracies in prediction, Aggarwal said. Sybill's AI promises to take care of the bulk of the repetitive, manual work involved in sales calls. It records sales conversations and then will provide a summary of the call, draft a follow-up email based on the salesperson's writing style, and provide context about the call. It can also update fields in CRMs like Salesforce and Hubspot; automatically summarize the budget, buyer, competition, buying process, and other relevant information (frameworks like BANT, MEDDICC and SPICED); and make all that information available to sales leadership. Sybill is going up against sales-specific tools, like Gong and Chrous.ai, and transcription tools like Otter, Fireflies, Fathom, and Zoom. But Aggarwal thinks there's a crucial element that sets his startup apart: "These are built like tools, not like an assistant, which is what we're doing," he said. "An assistant is someone you delegate entire tasks to, which is different from a tool that ingests some data and spits out insights. We also build end-to-end workflows to solve use cases like notetaking from calls, CRM entry and follow-ups." Aggarwal told TechCrunch that he met his co-founder, Nishit Asnani, at Stanford University's graduate school. A year later, they were joined by Soumyarka Mondal, the co-founder and CTO of Sybill, who had stints at Confluent, Morgan Stanley and Salesforce; and Mehak Aggarwal, Gorish's sister, who previously worked as a research fellow and led AI development at Harvard University and MIT. Founded in 2020, Sybill scaled its ARR from $100,000 to $1 million in ARR within 9 months in 2023, Aggarwal said, and most of that was apparently driven by referrals. Almost 60% to 70% of its new customers and new revenue come in either via direct referrals or from users who change jobs and bring Sybill into their new company, he told TechCrunch. The startup has already secured more than 500 paying customers (teams), Aggarwal said. These customers are spread across over 30 countries, but the majority are from the U.S., Canada, Australia, the U.K. and India. According to the CEO, the tech slowdown helped the startup grow its business as companies tried to cut costs and make their processes more efficient. "Sybill helps their seller save more than 5 hours every week, helps management get true visibility into what's going on, and improves the sales process efficiency," he said. The Series A round brings the company's total raised to $14.5 million since its inception in 2020. Existing investors Neotribe Ventures, Powerhouse Ventures, and Uncorrelated Ventures also participated in the round. The startup did not disclose its valuation. The company will use the new money to develop its AI assistant further reps and hire more staff. Sybill has 30 employees and plans to have about 40 staff by the end of this year.
TechCrunch
Wed, 31 Jul, 2:03 PM UTC
Google who? This new service actually gets AI search right
Time for a bit o' brutal honesty: Whenever I hear about a new search tool or info-surfacing service, my first reaction is to proactively cringe a little -- and then set my skepticism guard to its highest possible setting. Surely you've had this same sort of response by now, too -- right? Since the start of this whole generative-AI explosion, we've seen an endless parade of apps touting themselves as The Future of Searchâ„¢. And with very rare exception, more or less all of 'em share the same fatal flaw: They just aren't reliable. They serve up inaccurate info, with a shocking amount of confidence to accompany it. It's as true for the high-profile AI search tools by companies like Google and Microsoft as it is for the creations from small, scrappy startups. Today's tool is one of those rare exceptions. It's an AI-powered search app that's extremely specific in its purpose and the type of info it provides. In fact -- no exaggeration -- it might just be the most reliable, fact-driven search service you've ever encountered.
Fast Company
Sat, 10 Aug, 12:00 PM UTC
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