Anees Amjad

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

My work spans an internal AI assistant at Ourea Energy, a public-sector careers platform I co-founded, and research software. I’m pursuing an MS in Computational Analysis and Public Policy at the University of Chicago.

Selected workGet in touch

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

Ourea Brain

Company knowledge, accessible through Slack.

Fig. 1 · Explanatory diagram · simplified architecture

  1. Question in SlackA colleague asks about a project
  2. App on Google Cloud RunCredentials in Secret Managerbuilt by me
  3. Company context + Claude APISlack, Gmail, Google Docs, meeting notesbuilt by me
  4. Response in SlackThe answer is posted back
Fig. 1. How a question moves through Ourea Brain. Drawn for this page; not a screenshot of the internal tool.

What it does

An internal AI assistant that brings company context into Slack for colleagues at Ourea Energy, designed to help them retrieve project context, identify owners, and follow up on decisions.

What I built

As an Agentic AI Intern, I built and deployed the assistant: the Slack-connected app on Google Cloud Run, its connections to company sources, and its use of Anthropic’s Claude API.

Observed behaviour

An early live deployment answered a Slack question using meeting-note context. It is an internal tool with no public link.

ToolsSlack integration · Anthropic Claude API · Google Cloud Run · Google Workspace sources · meeting-note integration · Secret Manager

PublicPath

Making public-sector opportunities easier to find.

Fig. 2 · Left: explanatory diagram · Right: project artifact

  1. External job APIs
  2. Scheduled ingestionPython, run daily by GitHub Actionsmy work
  3. Data qualityClean, deduplicate, normalize, validatemy work
  4. Postgres on Supabase
  5. Search and filters on the site
PublicPath homepage with the headline ‘Your path into public service starts here’.

Project homepage, captured 6 Oct 2026: the team’s product. Project website ↗ Job search was not loading when checked on 6 Oct 2026.

Fig. 2. The data flow behind the listings (left), with my stages marked, beside the team’s homepage (right). The screenshot shows the product, not my backend work.

What it does

Helps students and early-career candidates explore government careers.

What I built

As co-founder (Engineering and Data) and one of two engineers, I worked on API ingestion and data quality: cleaning, deduplicating, normalizing, and validating listings for search and filtering.

Project artifact

The live project website and its homepage (Fig. 2, right).

ToolsPython · GitHub Actions · Supabase · Postgres

CLARITY

Turning clinical notes into patient-friendly explanations.

Fig. 3 · Explanatory diagram · pipeline sequence

  1. De-identified clinical noteJSON input
  2. Explanatory contentmy pipeline
  3. Narration and slidesMicrosoft Neural TTSmy pipeline
  4. MP4 videomy pipeline
Fig. 3. The sequence my Python pipeline automates. No clinical material is shown.

What it does

Part of CLARITY, a healthcare-AI research project at HOPE Lab, UChicago Booth: turning de-identified clinical notes into patient-friendly explanatory videos.

What I built

As a Research Assistant, I built the Python pipeline that automates explanatory content, narration, slide generation, and MP4 production.

Output

MP4 explanatory videos. Clinical material is not public, so no example is shown.

ToolsPython · Microsoft Neural TTS

Supporting work

Political Narrative Navigator team dashboard: monthly line charts comparing voter issue priorities with campaign speech topics in 2016, 2020, and 2024.
Fig. 4. Political Narrative Navigator dashboard, a team project at the University of Chicago; image from the team’s README. Team repository on GitHub ↗

  • Political Narrative Navigator

    Team project

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

  • Energy Market Intelligence

    Ourea Energy · separate from Ourea Brain

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

  • Chicago Eviction Risk

    Applied ML · private repository

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

Background

I combine software building with applied research in machine learning, survey analysis, and geospatial work.

  • 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, ML · 2025
  • CERP — Analyst · 2024–25
  • MS, Computational Analysis and Public Policy, UChicago · expected June 2027
  • BS, Economics and Political Science, Lahore School of Economics · May 2024