Anees Amjad

I build AI tools and data products for real-world decisions.

I’m Anees Amjad, a master’s student in Computational Analysis and Public Policy at the University of Chicago. My work includes an internal AI assistant at Ourea Energy, a public-sector careers platform I co-founded, and research tools that turn complex data into usable outputs.

Selected work Get in touch

Open to AI engineering roles, startup opportunities, and collaboration.

First case · Ourea Brain

An AI assistant in Slack

  1. Question asked in Slack
  2. App on Google Cloud Run built by me
  3. Relevant company context + Claude API
  4. Response in Slack
Simplified architecture. Read the Ourea Brain case ↓
Role
Builder · Agentic AI Intern, Ourea Energy
Status
Built and deployed internally
Tools
Slack integration, Anthropic Claude API, Google Cloud Run, Google Workspace sources, meeting-note integration, Secret Manager

Ourea Brain

Company knowledge, accessible through Slack.

ForColleagues at Ourea Energy who need project context, owners, and decisions without searching several tools.

I built and deployed Ourea Brain, an internal AI assistant that brings company context into Slack. It connects information across Slack, Gmail, Google Docs, and meeting notes to help colleagues retrieve project context, identify owners, and follow up on decisions.

How it works

  1. A colleague asks a question in Slack.
  2. The app on Google Cloud Run receives it; credentials are held in Secret Manager. my work
  3. It draws on relevant company context and calls Anthropic’s Claude API. my work
  4. The response is posted back in Slack.

Simplified architecture.

Evidence

An early live deployment answered a Slack question using meeting-note context.

Internal tool at Ourea Energy, so there is no public link.

Role
Co-founder, Engineering and Data; one of two engineers
Tools
Python, GitHub Actions, Supabase, Postgres

PublicPath

Making public-sector opportunities easier to find.

ForStudents and early-career candidates exploring government careers.

I co-built PublicPath, a platform helping students and early-career candidates explore government careers. My work focused on API ingestion and data quality: cleaning, deduplicating, normalizing, and validating listings for search and filtering.

How it works

  1. Listings come from external job APIs.
  2. Python ingestion is scheduled to run daily with GitHub Actions. my work
  3. Data-quality steps clean, deduplicate, normalize, and validate listings. my work
  4. Listings are stored in Postgres on Supabase.
  5. The site’s search and filters read from that store.

Simplified data flow.

Evidence

PublicPath homepage with the headline ‘Your path into public service starts here’.

Project homepage, captured 6 October 2026. It shows the team’s product; my part is the data flow on the left.

Project website ↗

Job search was not loading when checked on 6 Oct 2026.

Role
Research Assistant, HOPE Lab, UChicago Booth
Tools
Python, Microsoft Neural TTS

CLARITY

Turning clinical notes into patient-friendly explanations.

ForA healthcare-AI research project exploring patient-friendly explanations of clinical notes.

I built a Python pipeline for the CLARITY healthcare-AI project that converts de-identified clinical-note JSON into patient-friendly explanatory videos, automating narration, slide generation, and MP4 production.

How it works

  1. Input: a de-identified clinical note in JSON.
  2. The pipeline produces explanatory content from the note. my work
  3. Narration is generated with Microsoft Neural TTS, and slides alongside it. my work
  4. Both are assembled into an MP4 video. my work

Simplified pipeline sequence.

Evidence

Output format: MP4 explanatory videos.

Clinical material is not public, so no example is shown.

Supporting work

  • Energy Market Intelligence

    Ourea Energy · separate from Ourea Brain

    Built a weekly AI-assisted market-intelligence workflow that filtered 50+ recurring signals across energy storage, utilities, and data centers into leadership updates on competitors, investments, and partnerships.

  • Chicago Eviction Risk

    Applied machine learning · private repository

    Built an interpretable machine-learning and geospatial workflow to explore eviction-risk patterns in Chicago.

  • Political Narrative Navigator

    Team project, University of Chicago

    Analyzed 2,000+ presidential campaign speeches alongside YouGov data using AI-assisted text workflows.

    Team dashboard comparing voter issue priorities with campaign speech topics by month in 2016, 2020, and 2024. Political Narrative Navigator on GitHub ↗

    Dashboard image from the team’s README.

Background

I combine software building with applied research: AI tools and data platforms on one side; machine learning, survey analysis, and geospatial work on the other.

  • Ourea Energy — Agentic AI Intern · 2026–
  • Financial Health Network — Research Intern, Data Analytics · 2026–
  • HOPE Lab, UChicago Booth — Research Assistant · 2026–
  • PublicPath — Co-founder, Engineering and Data · 2026–
  • PAMS — Research Associate, Machine Learning · 2025
  • CERP — Analyst · 2024–2025
  • University of Chicago — MS, Computational Analysis and Public Policy · expected June 2027
  • Lahore School of Economics — BS, Economics and Political Science · May 2024