Generative AI is showing up more and more in workplaces, but not all executives know how to incorporate it and not all workers are confident about using it. That's where the startup Writer.ai sees an opportunity. 

As CIOs figure out how to make the most effective use of AI in their organizations, Writer offers off-the-shelf language models and natural language processing technology to expedite the process and enable employees to write blog posts and sales emails; create answers to frequently asked questions; and generate job and product descriptions with AI-enabled apps, no matter how technical they are.

This ideally will help smooth the transition to AI-enabled workflows. A June study from software company Freshworks found that staffers in IT departments are the most comfortable with AI, followed by those in marketing and finance. It's understandable that not everyone feels up to speed with AI, given the rapid onslaught of generative AI tools since AI startup OpenAI debuted its generative AI chatbot ChatGPT in 2022.

Companies like Adobe, Amazon, Anthropic and OpenAI are promoting their own enterprise-specific chatbots, with similar goals. But Writer wants to take chatting out of the equation.

Apps are the new chat

While mainstream chatbots work well for individual users, Writer CEO May Habib said these chat-based interfaces aren't a good fit for companies with a lot of different employees who will inevitably input different prompts for the same task and get different outputs.

A spokesperson referred to a broader "overchatification of AI."

"When people think of generative AI, they just think of chat, and there's so much more value you can unlock beyond chatwithin an enterprise organization," she said.

But there's still sort of a chat component with Writer apps.

When you interact with a mainstream chatbot, you have to "train" it first by telling it what you want. Writer's apps remove that step. So if, say, you wanted to generate headlines for blog posts, you could tell a Writer app you wanted it to think like an editor, and then you could show it examples of headlines you like and instruct it to create headlines that are pithy and will capture attention. Once you've established the ground rules with the app, you can simply input details about your article and it'll generate headlines without further chat thereafter.

"You're getting a lot more prescriptive about exactly what an end user needs to give the generative AI tool and what outputs come out of it," Habib said. 

Ask Writer and AI Studio

Customers of San Francisco-based Writer — which include consulting firm Accenture, financial software company Intuit, beauty brand L'Oreal, digital music service Spotify and ride-sharing platform Uber — can access apps in two ways.

They can use Ask Writer, an out-of-the-box chatbot, which the spokesperson described as "like ChatGPT but custom-built for the enterprise."

This comes with around 25 prebuilt apps, which run the gamut from generating recaps of transcripts to creating sales emails and error messages to performing image analysis.

Or customers can use AI Studio, which allows you to build your own apps with either a no-code building tool or through APIs, which enable developers to build new applications with Writer technology, and an open-source app development framework, which is a library of tools and code that developers can also use to create apps.

According to Writer, this allows employees to collaborate on custom apps no matter how tech-savvy they are.

"We say at Writer, 'If you can write it, if you can describe it, you can build it,'" Habib said.

LLMs and RAG

These apps are powered by Writer's own large language models, which are the AI models trained on huge datasets — though the spokesperson didn't disclose what they're trained on exactly — so they can understand and generate content. LLMs underpin mainstream chatbots like OpenAI's ChatGPT, Google's Gemini and Anthropic's Claude.

Estimates from gen AI startup Vectara show that mainstream models like GPT-4o, Llama 3.1 405B and Gemini 1.5 Flash hallucinate, or generate false or misleading content, anywhere from 1.3% to 7.4% of the time.

Writer contends this isn't good enough for enterprises, which need consistent accurate outputs. 

The spokesperson said Writer's family of LLMs are ranked by Stanford's Holistic Evaluation of Language Models, which rates AI models across metrics like accuracy, general information and bias.

In July, Writer added health care- and finance-specific LLMs.

The health care model was trained on patients' medical summaries, so it can help analyze them to inform clinical decision making. The financial model was trained on how to rebalance a portfolio so it can help do just that for clients.

"When we can work backwards from the use cases that we know customers will need, we can train the models really effectively and efficiently," Habib said.

Writer also has a general-purpose model and a model for vision analysis. The vision model can analyze images like charts and graphs, as well as sketches or handwritten notes.

In addition to these LLMs, Writer offers RAG, or retrieval augmented generation, a type of natural language processing for questions.

"When given a question, it retrieves contextually relevant data points from a large corpus of uploaded data and passes it to LLMs to generate an accurate answer," Writer said in a blog post.

The spokesperson said this allows Writer to ingest all of a company's data and link it to the LLM. The startup lets you download files of your own data with up to 10 million words, which it says is about 20,000 pages, to ask questions, do research or generate outputs.

"The value is in your own organization's information and data," she said. "And a lot of the industry has really struggled to create RAG solutions that are accurate enough for an enterprise to use."

The spokesperson didn't detail how Writer's RAG offering is more accurate.

Writer also provides AI guardrails, which are designed to help prevent the app from violating any legal or ethical rules.

Qordoba to Writer

A basic plan starts at $18 per user per month for up to five users. Writer offers custom pricing for enterprise users.

Habib and Writer co-founder and CTO Waseem Alshikh began working together on natural language processing, the branch of AI that allows machines to understand human language, and machine translation, which uses AI to translate text from one language to another, in 2013. They founded AI writing assistant Qordoba in 2015.

In 2017, the research paper "Attention is All You Need," which was published by researchers from Google and the University of Toronto, introduced the idea of transformers in machine translation. Transformers are a type of neural network, or a machine learning model that acts like the human brain, that changes an input into an output by learning context and tracking relationships between words.

Habib and Alshikh decided to pivot from straight language translation to translating business content into more usable content with this transformer-based approach and in 2020, they rebranded Qordoba as Writer and began working on LLMs.

Writer has raised $126 million to date, including $100 million in a Series B round in September.

Investors include venture firms Iconiq Growth, Balderton Capital, Insight Partners and Aspect Ventures, investment firm WndrCo and Writer customers Accenture and Vanguard.

"Always plan for more," Habib said of future funding.