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MyCapitol

How We Use AI

We think you deserve to know when AI is involved. Here's how it powers MyCapitol — the features you interact with, how we built the platform, and what to keep in mind when using it.

AI Features You'll Encounter

We use AI to make complex congressional data more understandable and accessible. Here's where you'll see it at work:

Billie AI Legislative Assistant

Our chat assistant helps you ask questions about bills, representatives, and policy in plain language. Billie can look up data, explain legislation, and help you prepare for advocacy.

What to know

Billie can misinterpret questions, return outdated information, or confidently state something incorrect. It may also miss nuances in complex policy areas.

Best practice

Treat Billie as a research starting point, not a definitive source. Cross-check specific claims — bill statuses, vote counts, dates — against Congress.gov. If something doesn't sound right, ask Billie to cite its source.

Bill Summaries

AI generates plain-language summaries of congressional bills so you don't have to parse dense legal text. These summaries aim to be accurate and nonpartisan.

What to know

Summaries may oversimplify provisions, omit important exceptions, or subtly shift emphasis in ways that don't fully reflect the bill's intent. Technical or highly specialized legislation is especially prone to inaccuracy.

Best practice

Use summaries to quickly decide if a bill is relevant to you, then read the full text for anything you plan to cite, share, or act on. Don't quote an AI summary as if it's the bill's language. If a summary looks wrong, hit the flag button next to it — we review every flag.

Semantic Search

When you search for bills or organizations, AI-powered embeddings help find conceptually related results — not just exact keyword matches. This surfaces relevant legislation you might otherwise miss.

What to know

Semantic search can surface surprising connections, but it can also return results that seem related but aren't, or miss relevant bills that use different framing. It's a complement to keyword search, not a replacement.

Best practice

Try multiple search approaches. If you're doing thorough research on a topic, combine semantic search with keyword filters, policy area browsing, and committee-based exploration to make sure you're not missing anything.

Policy Document Generation

Our Create tool uses AI to help you draft talking points, letters to representatives, testimony, and other advocacy documents grounded in real legislative data.

What to know

Generated documents are drafts, not finished products. They may contain factual errors, use generic language, or miss context that's specific to your situation. The AI writes persuasively, which can mask weak or inaccurate arguments.

Best practice

Always edit generated documents in your own voice. Verify every factual claim before sending anything to a legislative office. Add your personal story and specific ask — that's what makes advocacy effective, and AI can't do it for you.

Representative Summaries

AI generates biographical and legislative summaries for each member of Congress, pulling together career highlights, policy focus areas, and committee roles into a readable profile.

What to know

These summaries are generated from available data and may not capture recent developments, nuanced positions, or the full scope of a representative's record. They aim to be nonpartisan but may unintentionally emphasize certain aspects over others.

Best practice

Use rep summaries as a quick orientation, especially before a meeting or when researching someone new. For a complete picture, explore their sponsored bills, committee assignments, and voting record directly on their profile page. If something looks off, hit the flag button on their profile — we review every flag.

Endorsement & Oversight Letter Extraction

AI processes press releases, coalition letters, and congressional correspondence to extract which organizations endorse or oppose bills, and which representatives signed oversight letters. This powers the endorsement and oversight data you see throughout the platform.

What to know

Extraction from unstructured documents is inherently imperfect. AI may misclassify a position (e.g., reading a neutral mention as an endorsement), miss organizations from a long signatory list, or link an endorsement to the wrong bill version.

Best practice

Look for the Pending Human Review badge on endorsements — it means the data was AI-extracted and hasn't been verified by our team yet. Oversight letters go through a similar review process before we mark them as confirmed. If something looks wrong, let us know.

Data Quality Auditing

We use AI to audit our own data — checking for inconsistencies, flagging potential errors in imported records, and validating that the information we present matches official sources. This helps us maintain data quality across hundreds of thousands of records.

What to know

AI auditing catches a lot, but it's not perfect. Some data quality issues — especially subtle ones like outdated committee assignments or mismatched campaign finance records — may still exist in the platform.

Best practice

If a data point looks wrong or outdated, trust your instinct and verify it. We're continuously improving our data pipeline, and user reports are one of the most valuable ways we catch issues that automated checks miss.

Built with AI Assistance

We believe in practicing the transparency we preach. MyCapitol itself is built with significant help from AI coding tools.

Our development team uses AI assistants to write code, design features, debug issues, and iterate on the platform. This isn't a secret — it's a core part of how a small nonprofit team can build and maintain a platform of this scope.

AI-assisted development means we can move faster, but it also means imperfections are inevitable. You may encounter bugs, rough edges, or features that don't work exactly as expected. We take quality seriously and test everything before it ships, but we'd rather get useful tools into your hands quickly and improve them based on your feedback than wait for perfection.

Every piece of code goes through testing before it reaches you. We also use AI-powered security analysis tools that automatically scan our code for vulnerabilities as we write it — so AI helps us build, and also helps us build safely.

Why AI Matters for Civic Tech

Congressional data is public, but it isn't always accessible. Bills are written in legal language. Campaign finance records are buried in spreadsheets. Lobbying disclosures are scattered across databases. Understanding what your government is doing shouldn't require a law degree or a team of analysts.

AI helps us bridge that gap. It lets us summarize complex legislation, connect disparate data sources, and build search tools that understand what you're actually looking for. And it lets a small team punch well above its weight.

MyCapitol is a 501(c)(3) nonprofit. We don't have a large engineering team or venture capital funding. AI allows us to deliver a platform that would otherwise require resources far beyond what we have — and to keep it free for the advocates, researchers, journalists, and citizens who need it.

Let's Build This Together

We're building MyCapitol in the open because we believe civic tools should be shaped by the people who use them. Your feedback directly influences what we build next.

Found a bug? Something confusing? Have an idea for a feature that would help your advocacy work? We want to hear from you. This platform gets better every time someone tells us what's working and what isn't.