Monogram
11 projects
- AI Cloud
- Next.js
- Vercel
- Europe
- Latin America
- North America
Featured projects
Harvard NeuroLaw Library
The Opportunity: Harvard's CLBB NeuroLaw Library holds thousands of peer-reviewed articles, amicus briefs, court cases, and expert affidavits on neuroscience and law, open to anyone. The audience is judges, attorneys, families, and incarcerated people, and the source material is written at one expert reading level. Hand-writing simpler versions does not scale and goes stale on the next edit.
The Solution: When an editor publishes a document, a webhook converts it to Markdown and Gemini 2.5 Flash rewrites it at four reading levels under fixed rules, plus keywords and a forty-word summary. The output lands in the Contentful draft for review, and the reader moves one slider to switch levels with no model calls at request time. Semantic search runs on 3072-dimension Gemini embeddings alongside keyword matching, so a plain-language question finds the right brief. The library runs on Next.js and Vercel, with Contentful over GraphQL and Typesense for search.
The Impact: Critical neuroscience research is free, open, and readable at whatever level a person needs, with the original always one drag away and every resource carrying citations in five formats. The 2026 upgrade to Google's current GenAI SDK and concurrent generation cleared a backlog of 167 articles and 29 briefs and brought each document inside the 300-second limit. "Monogram was integral to designing the CLBB NeuroLaw Library at Massachusetts General Hospital. They are the best of the best." Stephanie Tabashneck, Founding Director.
Project expertise
- AI
- Integration Services
QuickNode Builder's Guide
The Opportunity: QuickNode's Builder's Guide was a hand-curated directory of Web3 tools. Each entry took hours of research, which capped how deep the directory could go.
The Solution: We designed the interface and a design system in Figma, then built a five-node LangGraph pipeline: Tavily search gathers a tool's site, docs, and social links, GPT-4o writes the profile with pricing tiers and use cases, a validation node checks categories against Contentful's definitions, a scoring node grades quality, and the result publishes straight to the CMS. The pipeline runs on Cloudflare Workers with a separate Next.js front end.
The Impact: The directory started at 700 tools and scaled past 5,000 entries, a 7x increase, with more than 60 structured fields generated per entry. Research that took hours now runs in minutes, with a measurable lift in SEO.
Project expertise
- AI
- Integration Services
CrewAI
The Opportunity: CrewAI is the platform enterprises use to build, orchestrate, and deploy teams of autonomous AI agents, with adoption across 63% of the Fortune 500. Leading a category needs a digital experience that speaks to the executive evaluating an agent management platform and to the engineer shipping a first production crew, and publishing that keeps pace with the product.
The Solution: We designed and engineered crewai.com as a marketing platform on Next.js and Contentful, a developer portal with OpenAPI 3.1 and Model Context Protocol (MCP) surfaces, and automated publishing infrastructure, deployed on Vercel. Built with Next.js, Contentful, GraphQL, TypeScript, and Vercel.
The Impact: One platform serves people and intelligent systems alike: readers get the marketing site, agents and developer tooling get structured, discoverable surfaces, and the CrewAI team publishes without waiting on a deploy.
Project expertise
- AI
- Design
- Integration Services
- UI/UX Development
Kasada
The Opportunity: Kasada protects enterprises from automated attacks, account abuse, and AI-driven threats. To serve enterprise buyers and machine consumers alike, it needed a platform that exposes structured data to search engines, developers, and AI assistants without slowing the human experience.
The Solution: We designed and engineered the site end to end: a Figma design system, modular content in Sanity, and discovery surfaces (llms.txt, sitemap.md, and .well-known endpoints) that give search engines and AI assistants structured access to the same content people read. Built with Next.js, Sanity, TypeScript, Tailwind CSS, HubSpot, and Vercel.
The Impact: A structured digital platform that reflects Kasada's own approach to the modern internet: know what to trust, make that information accessible, and build systems that can distinguish signal from noise.
Project expertise
- Design
- Integration Services
- UI/UX Development
About
Monogram is an Applied AI Studio based in Atlanta.
We design, build, and deploy the agents and AI apps that connect to real products, data, and operations, and we ship them on Vercel. In production that has meant agents executing real workflows end to end: voice agents answering live calls with responses in less than 2 seconds, 92% automation on a customer-facing workflow, and a nine-agent pipeline serving up to 1,000 users a day.
Design, engineering, and service work as one team. The interfaces and human-in-the-loop systems that make AI products people can trust, the agents, RAG, evals, and data pipelines that hold up in real business environments, and the discipline to move from idea to launch.
The depth is in our public case studies, which show the architecture, the model selection, and the tradeoffs behind each system. That is the work, not the wrapper. And the AI holds up because of what sits under it: we have shipped enterprise software since 2017 for IBM, Vercel, GitHub, a major developer platform, a US airline, and dozens of other teams, on Next.js and Vercel. The applied AI work sits on top of that engineering.
We build with the latest models and pick the right one for each workload instead of locking you to a single provider, then put them behind interfaces that never trade away speed. Systems run grounded in your data, at response times people will use.
Services
AI Systems
Production AI systems: assistants, agents, developer portals, and MCP servers. We build on the AI SDK, route models through the AI Gateway with failover, and run durable agents on Eve. Recent work includes a nine-agent pipeline that turns a use-case description into a working prototype in under four minutes (monogram.io/work/multi-agent-ai-solution-generator-for-a-developer-platform) and a platform that scores every one of a major US airline's support conversations with Claude (monogram.io/work/agentic-ai-for-customer-journey-intelligence).
- Multi-agent orchestration: specialized agents with single responsibilities, dynamic instruction injection, and programmatic validators where determinism matters. Separate evaluator and refiner agents keep generated output honest.
- Knowledge and analysis agents: agents grounded in your real data through RAG, vector stores, and live API access connected with the Model Context Protocol. The same foundation drives batch analysis at scale, scoring large volumes of content or conversations against your own rubrics with a full record of what shaped each result.
- Voice and conversational interfaces: voice and chat agents that answer live calls and respond in less than 2 seconds, built on AWS or GCP contact center infrastructure. The agent reads and writes to payment, inventory, and identity systems during the call and completes the transaction.
- Agent ops and evaluation: review queues, eval suites, telemetry, and regression tests that make agent behavior measurable instead of anecdotal. Low-confidence outputs route to people, drift gets caught before users feel it, and prompts, tools, and policies improve against real usage.
Engineering
Developer portals (monogram.io/work/crew-ai), web apps, and content platforms on Next.js, with the integration work underneath: CMS and GraphQL layers, search via Algolia, relational database such as Supabase or Neon, MCP and OpenAPI surfaces, webhooks and revalidation, and a performance budget the build has to meet. Frameworks we ship on Vercel: Next.js, React, Astro, and Svelte.
Design
Brand identity, design systems, and the interfaces AI products need: agent dashboards, review queues, and confidence states. We design in Figma against the components that will exist in the codebase, so handoff is a checklist rather than a translation.
How we use Vercel
Vercel is not where we host, it is the platform we build on, and we have been on it since it was Zeit. Monogram was Vercel's first agency partner, and Vercel is a client as well as a partner. Every AI system we ship needs a surface people actually use, and that surface is a Next.js app on Vercel: dashboards, chat, live previews, and review queues. We build agent orchestration on the Vercel AI SDK, route models through the AI Gateway with failover, and run durable agents on Eve, which is what the assistant on monogram.io runs on. Acceptance testing happens in the deployment with Vercel Comments, revalidation webhooks publish content without a build, and Vercel Firewall rules handle rate limiting on our internal tools. We also ship client sites agent ready: answers in server-rendered HTML, agent crawlers unblocked, accurate status codes, and a linked llms.txt and Markdown mirror. Where the web is going, agents reading it alongside people, is where Vercel is already pointed, and it is where we build.
Our ideal project
We do our best work where engineering and design have to hold up together, and where AI has to connect to real systems.
- An AI feature that has to reach production: an assistant, an agent, a developer portal with MCP, or a knowledge base with grounded citations.
- A workflow that ties up expert time, document review, customer conversations, reconciliation, evaluation, that agents could run end to end with the right guardrails.
- A platform with real engineering underneath: a developer portal, a content platform with structured data and search, or a web app whose integrations have to stay correct.
- A brand and product designed together, from identity and design system through the component library and the AI interface.
- A content operation that needs to publish without a deploy, with previews, comments, and instant rollback.
- Teams that want honest answers about what the platform can and cannot do.
Certifications
- Vercel Certified Solution Partner, Platinum
- Next.js Certified
- AI Cloud Certified
- Agent Foundations Certified (completed in New York, June 2026)
- Claude Certified Architect by Anthropic