Author, a San Francisco-based synthetic intelligence startup, is launching a unified AI agent platform designed to let any worker automate advanced enterprise workflows with out writing code — a functionality the corporate says distinguishes it from consumer-oriented instruments like Microsoft Copilot and ChatGPT.
The platform, known as Author Agent, combines chat-based help with autonomous process execution in a single interface. Beginning Tuesday, enterprise prospects can use pure language to instruct the AI to create displays, analyze monetary information, generate advertising and marketing campaigns, or coordinate throughout a number of enterprise methods like Salesforce, Slack, and Google Workspace—then save these workflows as reusable "Playbooks" that run robotically on schedules.
The announcement comes as enterprises wrestle to maneuver AI initiatives past pilot applications into manufacturing at scale. Author CEO Could Habib has been outspoken about this problem, lately revealing that 42% of Fortune 500 executives surveyed by her firm mentioned AI is "tearing their firm aside" on account of coordination failures between departments.
"We're delivering an agent interface that’s each extremely highly effective and radically easy to rework particular person productiveness into organizational affect," Habib mentioned in a press release. "Author Agent is the distinction between a single gross sales rep asking a chatbot to put in writing an outreach e mail and an enterprise guaranteeing that 1,000 reps are all sending on-brand, compliant, and contextually-aware messages to focus on accounts."
How Author is placing workflow automation within the palms of non-technical employees
The platform's core innovation facilities on making workflow automation accessible to non-technical workers—what Author executives name "democratizing who will get to be a builder."
In an unique interview with VentureBeat, Doris Jwo, Author's director of product administration, demonstrated how the system works: A consumer sorts a request in plain English — for instance, "Create a two-page partnership proposal between [Company A] and [Company B], make it a branded deck, embrace affect metrics and partnership tiers."
The AI agent then breaks down that request into discrete steps, conducts net analysis, generates graphics and charts on the fly, creates particular person slides with sourced data, and assembles an entire presentation. Your entire course of, which could take an worker hours or days, will be accomplished in 10-12 minutes.
"The agent principally appears to be like on the request, breaks it down, does analysis, understands what items it wants, creates an in depth plan at a step-by-step degree," Jwo defined throughout a product demonstration. "It’d say, 'I must do net analysis,' or 'This consumer wants data from Gong or Slack,' and it reaches out to these connectors, grabs the info, and executes the plan."
Crucially, customers can save these multi-step processes as Playbooks—reusable templates that colleagues can deploy with a single click on. Routines permit these Playbooks to run robotically at scheduled intervals, primarily placing data work "on autopilot."
Safety and compliance controls: Author's reply to enterprise IT issues
Author positions these enterprise-focused controls as a key differentiator from opponents. Whereas Microsoft, OpenAI, and Anthropic supply highly effective AI capabilities, Author's executives argue these instruments weren't designed from the bottom up for the safety, compliance, and governance necessities of enormous regulated organizations.
"All the merchandise you talked about are nice merchandise, however even Copilot could be very a lot targeted on private productiveness—summarizing e mail, for instance, which is essential, however that's not the part we're specializing in," mentioned Matan-Paul Shetrit, Author's director of product administration, in an unique interview with VentureBeat.
Shetrit emphasised Author's "belief, safety, and interoperability" method. IT directors can granularly management what the AI can entry — as an example, stopping market analysis brokers from mentioning opponents, or proscribing which workers can use net search capabilities. All exercise is logged with detailed audit trails exhibiting precisely what information the agent touched and what actions it took.
"These fine-grained controls are what make merchandise enterprise-ready," Shetrit mentioned. "We will deploy to tens of hundreds or tons of of hundreds of workers whereas sustaining the safety and guardrails you want for that scale."
This structure displays Author's origin story. Not like OpenAI or Anthropic, which began as analysis labs and later added enterprise choices, Author has focused Fortune 500 corporations since its 2020 founding. "We're not a analysis lab that went to shopper and is dabbling in enterprise," Shetrit mentioned. "We’re firstly focusing on the World 2000 and Fortune 500, and our analysis is in service of those prospects' wants."
Inside Author's technique to attach AI brokers throughout enterprise software program methods
A essential technical part is Author's method to system integrations. The platform consists of pre-built connectors to greater than a dozen enterprise functions—Google Workspace, Microsoft 365, Snowflake, Asana, Slack, Gong, HubSpot, Atlassian, Databricks, PitchBook, and FactSet—permitting the AI to retrieve data and take actions throughout these methods.
Author constructed these connectors utilizing the Mannequin Context Protocol (MCP), an rising commonplace for AI system integrations, however added what Shetrit described as an "enterprise-ready" layer on prime.
"We took a first-principle method of: You’ve got this MCP connector infrastructure—how do you construct it in a method that's enterprise-ready?" Shetrit defined. "What we’ve got right now within the business is unquestionably not it."
The system can write and execute code on the fly to deal with sudden situations. If a consumer uploads an unfamiliar file format, as an example, the agent will generate code to extract and course of the textual content with out requiring a human to intervene.
Jwo demonstrated this functionality with a each day workflow she runs: Each morning at 10 a.m., a Routine robotically summarizes her Google Calendar conferences, identifies exterior contributors, finds their LinkedIn profiles, and sends the abstract to her by way of Slack — all with out her involvement.
"This was fairly easy, however you may think about for a salesman it’d say, 'On the finish of the day, wrap up a abstract of all of the calls I had, ship me motion gadgets, put up it to the account-specific Slack channel, and tag these people to allow them to accomplish these workflows,'" Jwo mentioned. "That may run repeatedly every day, every week, or on demand."
From mortgage lenders to CPG manufacturers: Actual-world AI agent use instances throughout industries
The platform is attracting prospects throughout a number of industries. New American Funding, a mortgage lender, makes use of Author Agent to automate advertising and marketing workflows. Senior Content material Advertising Supervisor Karen Rodriguez uploads Asana challenge tickets with artistic briefs, and the AI executes duties like updating e mail campaigns or reworking articles into social media carousels, video scripts, and captions.
Different use instances span monetary companies groups creating funding dashboards with PitchBook and FactSet information, shopper packaged items corporations brainstorming new product strains primarily based on social media traits, and advertising and marketing groups producing partnership displays with branded property.
Author has added prospects together with TikTok, Comcast, Keurig Dr Pepper, CAA, and Aptitude Well being, becoming a member of an present base that features Accenture, Qualcomm, Uber, Vanguard, and Marriott. The corporate now serves greater than 300 enterprises and has secured over $50 million in signed contracts, with projections to double that to $100 million this 12 months.
The startup's web retention price — a measure of how a lot present prospects develop their utilization — stands at 160%, that means prospects on common enhance their spending by 60% after preliminary contracts. Twenty prospects who began with $200,000-$300,000 contracts now spend about $1 million yearly, in response to firm information.
'Vibe working': Author's imaginative and prescient for AI-powered productiveness past coding
Author executives body the platform as enabling what they name "vibe working" — a playful reference to the favored time period "vibe coding," which describes AI instruments like Cursor that dramatically speed up software program growth.
"We used to name it transformation once we took 12 steps and made them 9. That's optimizing the world as it’s," Habib mentioned at Author's AI Leaders Discussion board earlier this month, in response to Forbes. "We will now create a brand new world. That’s the greenfield mindset."
Shetrit echoed this framing: "Vibe coding is the theme of 2025. Our view is that ‘vibe working’ is the theme of 2026. How do you carry the identical productiveness beneficial properties you've seen with coding brokers into the workspace in a method that non-technical customers can maximize them?"
The platform is powered by Palmyra X5, Author's proprietary massive language mannequin that includes a one-million-token context window — among the many largest commercially out there. Author educated the mannequin for roughly $700,000, a fraction of the estimated $100 million OpenAI spent on GPT-4, by utilizing artificial information and methods that halt coaching when returns diminish.
The mannequin can course of a million tokens in about 22 seconds and prices 60 cents per million enter tokens and $6 per million output tokens — considerably cheaper than comparable choices, in response to firm specs.
Making AI Choices Seen: Author's Strategy to Belief and Transparency
A particular side of Author's method is transparency into the AI's decision-making course of. The interface shows the agent's step-by-step reasoning, exhibiting which information sources it accessed, what code it generated, and the way it arrived at outputs.
"There's a really clear exhibition of how the agent is considering, what it's doing, what it's touching," Shetrit mentioned. "That is essential for the top consumer to belief it, but additionally essential for the IT particular person or safety skilled to see what's occurring."
This "supervision" mannequin goes past easy observability of API calls to embody what Shetrit described as "a superset of observability" — giving organizations the power to not simply monitor however management AI habits via insurance policies and permissions.
Session logs seize all agent exercise when enabled by directors, and customers can submit suggestions on each output to assist enhance system efficiency. The platform additionally emphasizes offering sources and citations for generated content material, permitting customers to confirm data.
"With any type of chat assistant, agentic or not, belief however confirm is actually essential," Jwo mentioned. "That's a part of the pillars of us constructing this and making it enterprise-grade."
What Author Agent Prices—and Why It's Included within the Base Platform
Author is together with all the brand new capabilities—Playbooks, Routines, Connectors, and Character customization—as a part of its core platform with out extra expenses, in response to Jwo.
"That is totally included as a part of the Author platform," she mentioned. "We're not charging extra for utilizing Author Agent."
The "Character" function permits particular person customers, groups, or complete organizations to customise the AI's communication model, guaranteeing generated content material matches model voice and tone tips. This works alongside company-level controls that implement terminology and magnificence necessities.
For extremely structured, repetitive duties, Author additionally gives a library of greater than 100 pre-built brokers and an AI Studio for constructing customized multi-agent methods aligned with particular enterprise use instances.
The Race to Outline Enterprise AI: Can Function-Constructed Platforms Beat Tech Giants?
The launch crystallizes a elementary pressure in how enterprises will undertake AI at scale. Whereas consumer-facing AI instruments emphasize particular person productiveness beneficial properties, corporations want methods that work reliably throughout hundreds of workers, combine with present software program infrastructure, keep regulatory compliance, and ship measurable enterprise affect.
Author's wager is that these necessities demand purpose-built enterprise platforms moderately than shopper instruments tailored for enterprise use. The corporate's $1.9 billion valuation — achieved in a November 2024 funding spherical that raised $200 million — suggests buyers see benefit on this thesis. Backers embrace Premji Make investments, Radical Ventures, ICONIQ Progress, Salesforce Ventures, and Adobe Ventures.
But the aggressive panorama stays formidable. Microsoft and Google command monumental distribution benefits via their present enterprise software program relationships. OpenAI and Anthropic possess analysis capabilities which have produced breakthrough fashions. Whether or not Author can keep its differentiation as these giants develop their enterprise choices will take a look at the startup's core premise: that serving Fortune 500 corporations from day one creates benefits that analysis labs turned enterprise distributors can not simply replicate.
"We're coming into an period the place in the event you can describe a greater method to work, you may construct it," Jwo mentioned. "The brand new Author Agent democratizes who will get to be a builder, empowering the operational consultants and inventive problem-solvers in each division to turn out to be the architects of their very own transformation. That's the way you unlock innovation that opponents can't replicate."
The promise is alluring — AI capabilities highly effective sufficient to rework how work will get accomplished, accessible sufficient for any worker to make use of, and managed sufficient for enterprises to deploy safely at scale. Whether or not Author can ship on that promise on the pace and scale required will decide if its imaginative and prescient of "vibe working" turns into the 2026 theme Shetrit predicts, or simply one other formidable try to unravel enterprise AI's execution drawback.
However one factor is definite: In a market the place 85% of AI initiatives fail to flee pilot purgatory, Author is betting that the winners gained't be the businesses with essentially the most highly effective fashions—they'll be those that make these fashions really work contained in the enterprise.
