Primary AI development partner for Narratize's earliest generative features: document ingestion, technical briefs, research reports and scientific analysis.
Pass rate on the content-writing evaluation, up from 60%
88%
Every change scored automatically on GitHub Actions
CI evals
OpenAI, Anthropic and Mistral in one platform
Multi-model
Speak an idea, hear a narrated story back
Voice agent
The starting point
The challenge
Product innovation teams spent weeks turning research, internal documents and scattered ideas into technical briefs and decision-ready reports. Narratize needed generative features that experts would trust: grounded in their own sources, consistent in structure and fast enough to use every day.
The solution
What we built
Worked as the platform's primary AI development partner, turning the product vision into working AI capabilities for its earliest features.
Built document ingestion that brings research papers, internal files and notes into a structured knowledge layer.
Designed generation workflows for technical briefs, research reports and scientific analyses, combining OpenAI, Anthropic and Mistral models.
Connected research sources such as PubMed and arXiv, so drafts can draw on published work.
Added a voice storytelling agent: users speak, and hear a narrated, AI-generated story back, using Deepgram speech-to-text and text-to-speech.
Architecture
How the system works
How it fits together Data flow
01SourcesDocuments, notes, PubMed, arXiv
02IngestParse and structure knowledge
03GenerateBriefs, reports, analyses
04Model layerOpenAI, Anthropic, Mistral
05EvaluateCI suites on GitHub Actions
06DeliverDrafts in the product, or by voice
Engineering
How it was engineered
Ran evaluation suites in CI on GitHub Actions, so every prompt or pipeline change was scored automatically. This was before LangSmith was mature enough to rely on.
Built the evaluation sets from curated examples of briefs and reports, and kept them in the repository alongside the code.
Supported releases across time zones, including late-night fixes when the client team needed them.
“I value your skill and dedication to your craft… I've worked with a lot of engineers over my career and have seen all different types, and I'm happy we found a group like yours which is of the highest quality.”
Engineer on the client teamNarratize · via Slack
“[Our co-founder] was a thoughtful and collaborative partner who took the time to understand what we were trying to build and the problems we wanted to solve. [He] helped translate our product vision into working AI capabilities, contributing to the development of some of Narratize's earliest product features.”
Former executiveNarratize · via LinkedIn
“I want to send a huge thank you to everyone who worked on making this feature possible, through all the troubleshooting and problem solving. It's so exciting to finally have this live and in front of users!”
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