WRITER

WRITER is an enterprise AI company building a platform for organizations to create, deploy, and supervise AI agents across real business workflows. Founded in 2020 by CEO May Habib and CTO Waseem AlShikh, the San Francisco-based company has moved well beyond its early identity as an AI writing product.

The current platform combines WRITER Agent, Playbooks, Skills, Connectors, Knowledge Graph, AI Studio, and the Palmyra family of models. Together, those components are meant to connect AI with company knowledge, enterprise systems, operating standards, and governance controls instead of leaving each employee to improvise with a general-purpose chatbot.

That distinction matters because enterprise AI is entering a less glamorous and more consequential phase. The question is no longer whether a model can generate an impressive answer. The question is whether an organization can turn that capability into dependable work without losing control of data, permissions, quality, or accountability.

About WRITER

May Habib and Waseem AlShikh began working together on enterprise language problems in 2013, when they built a company focused on dynamically localizing business content. Their experience with machine translation gave them an early view of the transformer architecture that would later reshape natural language processing, and they launched WRITER in 2020 to apply that shift to enterprise work.

May Habib serves as CEO, while Waseem AlShikh serves as CTO. Their long working relationship is more than founder biography. Building AI for large organizations requires technical depth, product discipline, and the patience to navigate security reviews, deployment constraints, change management, and the gap between a successful pilot and a system people actually use.

WRITER's current leadership team also includes operating executives across revenue, marketing, finance, operations, people, customer success, security, and strategy. That breadth reflects the nature of the category: enterprise AI is becoming as much an implementation and organizational challenge as a model-development race.

From AI Writing to AI-Powered Work

The easiest way to misunderstand WRITER is to stop at its name. The company began with language and content use cases, but its current product is designed around AI agents that can execute multi-step work using corporate data and connected business systems. WRITER Agent is the main interface, while Playbooks define repeatable workflows and Skills encode specialized methods that teams want the agent to apply consistently.

Connectors link the platform to enterprise tools and data sources. Knowledge Graph grounds outputs in company information, and the Palmyra model family provides the underlying intelligence. AI Studio gives technical and business teams a way to build and manage applications, while enterprise controls are designed to determine what agents can access, which actions they can take, and how their work is reviewed.

That structure is WRITER's central bet. The model matters, but the durable value sits in the full operating layer around it: context, tools, repeatable processes, permissions, evaluation, supervision, and integration with the systems where work already happens.

Why Workflow Density Matters

In July 2026, WRITER reported that its customers had created more than 28,000 playbooks. The company cited Clorox, KPMG, and Metro Bank as examples of organizations using those playbooks for work such as campaign personalization, AI visibility, and account insights. Because the figure comes from WRITER, it should be read as a company-reported adoption metric rather than an independently audited market measure.

Even with that qualification, the metric is useful. A playbook represents a move away from one-off prompting toward a repeatable process that can be tested, shared, refined, and governed. That is closer to how enterprises operationalize software than the personal-chat pattern that defined the first wave of generative AI adoption.

Workflow density also changes the competitive question. Access to capable models is increasingly broad, but converting institutional knowledge into reliable execution remains difficult. The platform that makes those workflows easier to build, safer to run, and clearer to audit can occupy a more durable position than a tool that produces an isolated answer.

Capital, Customers, and Enterprise Credibility

WRITER raised a $200M Series C at a $1.9B valuation in November 2024. Premji Invest, Radical Ventures, and ICONIQ Growth co-led the round, with participation from a wider group that included Adobe Ventures, B Capital, Citi Ventures, IBM Ventures, Salesforce Ventures, and Workday Ventures. TechCrunch reported that the financing brought WRITER's total funding to $326M.

The capital gives WRITER room to compete in a category that demands expensive research, enterprise-grade infrastructure, and high-touch deployment capability. The investor list also includes companies that understand enterprise software distribution and adoption, although financial backing alone does not prove product leadership.

WRITER says hundreds of enterprises use its technology. Its current customer materials feature organizations including Vanguard, Salesforce, KPMG, Qualcomm, American Eagle, Uber, Dropbox, e.l.f. Cosmetics, and SCAN Health Plan. These examples support the company's enterprise focus, but they should not be read as blanket endorsements of every product claim or use case.

Trust Is Part of the Product

Enterprise agents are useful only if organizations can control what they know and what they do. WRITER's trust and security materials describe role-based permissions, audit logs, activity traces, approval flows, encryption, identity controls, data-retention settings, and deployment options designed for large and regulated organizations. The company also states that it does not train its models on customer inputs or outputs.

Those are official product and compliance claims, not an independent security assessment. Still, the architecture points to the right market pressure. As agents move from drafting text to touching CRMs, data warehouses, content systems, and operational tools, governance stops being a procurement appendix and becomes part of the core user experience.

This is where WRITER's full-stack approach may create leverage. A company that owns the model layer, grounding system, workflow surface, integrations, and supervisory controls can make those pieces work together. The tradeoff is that it must prove the whole system is reliable enough for mission-critical use, not merely that each component looks persuasive in a demo.

Culture and Hiring as Market Signals

WRITER's careers page is active and links to current open positions. The company describes its values as Connect, Challenge, and Own, emphasizing relationships, high standards, conflicting points of view, and long-term ownership. It also describes a hybrid work model and benefits that include health coverage, parental leave, stock options, retirement contributions, learning support, and paid time off.

The more important story is why the company is hiring. Enterprise AI deployments require researchers and engineers, but they also require security, customer success, operations, sales, finance, and implementation leadership. WRITER's expanded operating team suggests the category is moving from model experimentation toward the hard work of adoption across large organizations.

Hiring momentum should not be confused with a guarantee of growth, and live job listings change too quickly to freeze into a durable article. It is better understood as an operating signal: WRITER is preparing for a market in which customers expect not just access to AI, but support in redesigning workflows around it.

The Bigger Enterprise AI Shift

The first phase of generative AI rewarded novelty. The next phase will reward systems that can turn organizational knowledge into action without forcing companies to choose between speed and control. WRITER is positioning itself for that transition by treating agents as governed participants in work rather than smarter text boxes.

The company's name now functions almost like a misdirection. WRITER still begins with language, because language is how people describe goals, rules, and decisions. Its larger ambition is to turn those descriptions into repeatable execution across the enterprise, with humans defining the standards and software carrying more of the operational load.

That is a meaningful strategic position, but it comes with a demanding test. WRITER must show that its agents can remain accurate, observable, secure, and useful over long-running workflows inside complex organizations. If it can, the company will be competing for something larger than the AI assistant budget: a place in the operating architecture of enterprise work.