WRITER
Building the AI-Native Enterprise, One Agent at a Time

In the expanding world of generative AI, only a few companies have carved out a place as unique and resolute as WRITER.

Positioned at the forefront of enterprise AI transformation, WRITER has gone beyond building technology for large organizations—they’ve built it with them. Through thousands of hours working side by side with customers, a deep understanding of enterprise complexity, and a refusal to settle for retrofitted solutions, it created a platform purpose-built for the nuanced demands of modern businesses.

WRITER emerged in 2020 prior to the generative AI boom. At that time, the field was still largely academic and experimental, with major players targeting consumers or hobbyist developers.

But Waseem AlShikh, CTO and Co-founder, and May Habib, CEO and Co-founder, saw a different path forward. Initially working in machine translation, the two were convinced that language models would do more than just generate text—they would redefine the very fabric of work.

“We saw firsthand how transformer models changed the way language and, eventually, work happened,” says AlShikh. “From the beginning, we were building toward a future that was enterprise-first, not consumer-led.”

“We built WRITER to bring AI into the enterprise in a way that actually works at scale”

That early insight now underpins everything WRITER does. From foundational architecture to the interface end-users interact with, its platform is designed as an “AI HQ,” where business and IT teams can collaboratively build, deploy and manage intelligent agents at scale. It is a platform that reimagines how work gets done, integrating AI not as an accessory, but as an engine of productivity, control and insight.

Production-Level Deployments with Measurable Impact

Setting WRITER apart is its obsessive alignment with the real needs of large organizations. This isn’t just marketing spin; it is baked into their development process. Every product upgrade, every new feature, and every leap in capability stems from intimate engagement with enterprises. Accenture, Vanguard, Uber, Prudential and many more have shaped the contours of WRITER’s platform. WRITER listens, builds, iterates and listens again.

That loop of co-creation is most visible in the company’s decision to build its own, frontier large language models (LLM), rather than rely on open-source or third-party offerings. WRITER’s Palmyra family of LLMs—including its newly released Palmyra X5—are some of the only models in the world purpose-built for enterprise performance. They are engineered for mission-critical workflows in regulated industries, with context windows large enough to capture entire datasets, fast inference for real-time applications, and governance an integral part of every level.

The results speak volumes. Salesforce deployed WRITER across 3,000 employees and saw a 20 percent productivity boost, equivalent to saving an entire workday per employee each week. Vanguard achieved a 57 percent faster time to market with the platform. Kenvue rolled it out to more than 2,000 employees across 14 global brands, significantly reducing agency costs. These aren’t science projects or pilot programs. They are production-level deployments with measurable impact.

Bringing AI into the Enterprise

At the heart of this success is an end-to-end platform. WRITER’s AI HQ is more than a model playground. It’s a unified space where enterprises can design intelligent agents using pro-code or low-code tools, access a library of prebuilt, industry-specific agents, and supervise deployments with robust governance and observability. A fully integrated retrieval augmented generation (RAG) system, the Knowledge Graph uses proprietary data to ensure agents are both fluent and accurate by anchoring in proprietary company data.

“Most enterprises are approaching AI like any other software rollout,” explains AlShikh. “But retrofitting legacy SaaS systems for AI results in technical debt and marginal gains. We built WRITER to bring AI into the enterprise in a way that actually works at scale.”

That belief—that AI must be built in, not bolted on—guides everything. It’s why Agent Builder lets teams stitch together logic, data sources, and workflows using a secure, composable architecture. It’s why process blueprints act as orchestration layers that guide agents step-by-step through complex enterprise environments. And it’s why governance tools within the platform provide IT with the visibility and control needed to ensure compliance, accuracy and safe deployment.

Vertical AI Strategy

WRITER’s architecture does more than serve IT power users. It empowers everyone. Agents are easily discoverable through a personalized homepage. Whether built by WRITER, by users’ internal teams, or customized by individuals, these agents show up where people do their work. That level of intuitive design drives adoption, which in turn drives ROI.

We’re not just shipping great technology. We’re showing up as real partners. That means being on-site, rolling up our sleeves, and staying close, not just at the start, but throughout the journey

Adoption also depends on relevance. A one-size-fits-all approach rarely meets the needs of enterprise departments operating under unique pressures. WRITER built a vertical AI strategy that delivers domain-specific workflow solutions to every sector, from financial services to healthcare, and retail to CPG.

In finance, WRITER agents summarize broker research, track ESG regulations, and analyze SEC filings. In healthcare, they interpret insurance plans, summarize medical records, and extract insights from regulatory documents. In CPG and retail, they generate product content, analyze customer sentiment, and localize messaging in dozens of languages. These agents are built based on proven use cases of real WRITER customers.

The backbone of this vertical strategy is specialized language models like Palmyra Fin and Palmyra Med. These models are trained on curated data specific to their industries, making them capable of handling regulated content and high-stakes decisions. In recent benchmarks, Palmyra Med achieved 85.9 percent accuracy on medical tasks, while Palmyra Fin outperformed 23 other models in finance-related accuracy.

Showing up as Real Partners

WRITER’s obsession with accuracy has led to another major leap: self-evolving models that do more than processing static prompts. They learn and adapt in real time to the workflows, decisions and institutional knowledge of the organization. They don’t require constant reconfiguration, because they evolve with the business. It’s a model evolution path that WRITER believes is better suited to enterprise demands than the current trend of ever-larger reasoning models, which often introduce high latency, spiraling costs, and brittle performance.

“You can’t keep throwing more parameters at the problem and expect better performance,” AlShikh says. “Self-evolving models break through that limit. They adapt, remember and co-evolve with the organization.”

WRITER's approach to model development has led to industry breakthroughs with Palmyra X5. With a one-million-token context window and sub-second loop completion speeds, the model is capable of reasoning across vast enterprise datasets without chunking or degradation. According to WRITER, it performs nearly as well as GPT-4.1 on recall, costing three to four times less per token. That combination—speed and price—makes real-time, multi-agent orchestration possible, at scale.

Customers are already capitalizing on this. Uber uses AI agents to classify Slack and Jira support tickets, assess urgency, generate documentation, and publish updates—all without manual handoffs. AdoreMe, a women’s fashion brand, employs WRITER agents to validate returns, correct formatting, and personalize customer responses, freeing agents for more complex interactions. Commvault has transformed its RFP response workflow, with WRITER agents pulling documents, setting up collaboration channels, and drafting tailored responses in record time.

These are more than just clever use cases—they’re the foundation of a new kind of work. In WRITER’s vision, enterprise AI is not about novelty. It’s about orchestration, about moving beyond outputs to outcomes, and about treating AI as an active partner in business transformation.

That’s why WRITER goes beyond software delivery. Its team offers implementation support, change management, training, and co-creation services. The goal isn’t to drop off tools and disappear; it’s to become a partner in transformation. According to a recent WRITER research report, 98 percent of C-suite leaders believe AI vendors should help shape the vision for AI at work. WRITER has taken that to heart.

“We’re not just shipping great technology,” says AlShikh. “We’re showing up as real partners. That means being on-site, rolling up our sleeves, and staying close, not just at the start, but throughout the journey.”

AI Is No Longer an Option—It’s a Business Imperative

As generative AI moves from hype to utility, WRITER’s enterprise-first, customer-driven approach is paying off. With hundreds of Fortune 1000 companies onboard, a suite of proprietary models leading the market, and a platform designed for scale and adoption, it is positioned as an architect of the AI-native enterprise.

In the end, WRITER’s story isn’t about AI for its own sake. It’s about what happens when intelligent systems are built directly into the heart of the business—systems that learn adapt and evolve with their human counterparts. That’s not science fiction. It’s the new standard for enterprise productivity, and WRITER is writing the manual.

As enterprises worldwide seek to integrate AI at scale, WRITER is expanding its global presence, bringing its AI solutions to new markets like London and APAC. The next frontier is autonomous enterprise AI agents, with WRITER's first globally available super agent. These agents automate entire workflows across financial services, healthcare and retail, executing sophisticated, multi-step processes without human intervention.