1ST SOURCE CORP

This is an inventory of our records, not an assessment of SRCE. It says nothing about how SRCE appears inside ChatGPT, Claude or any other AI product — nothing outside those systems can measure that, and we will not pretend otherwise.

What Origin Can Add

Retrieved from Origin

Live means a person's assistant fetched this record on their behalf. Crawlers are indexing bots. The rest is browser and API traffic. These count requests to Origin — they are not a measure of how often anyone asks an AI about SRCE, and we have no way to measure that.

What It Took to Build This Record

A machine cannot check a PDF against anything. Turning 1ST SOURCE CORP's filings into a signed, structured record that anyone can verify took the work below — and this is what a reader gets in return.

What Origin Invested

How hard this site was for us to read

Hard

Our extractor needed bespoke scripts and several attempts. This describes our extraction effort, not a grade for SRCE.

SEC EDGAR extraction	272 filings indexed
AI profile generation	~$0.10 (Claude Sonnet)
IR site scraping	Custom Claude Code scripts
Manual engineering time	2-3 days, multiple attempts
Deep scraper development	Subpage navigation + retries
Stock quote pipeline	Daily EOD automated
Origin chain signing	Every response anchored

Your IR site required significant engineering effort — custom Claude Code scripts, manual debugging, and multiple attempts over days. This is real human + AI time that most investors will never spend.

With Origin (same review)

Company identity	~200 tokens
Full profile (people, products)	~800 tokens
Filing index (272 filings)	~500 tokens
Stock quote with provenance	~150 tokens
Earnings facts	not captured
Topic search (cross-company)	~300 tokens
Total per review	~2,450 tokens
Time to answer	2–4 seconds
Cost per query	< $0.01
Provenance	Full chain to SEC.gov

4-5 API calls. Structured JSON. Every response signed. Agent gets exactly what it needs — not a 200-page PDF.

We spent days making 1ST SOURCE CORP AI-accessible. Most agents won't.

Our team wrote custom extraction scripts, debugged JavaScript-rendered pages, and ran multiple scraping sessions over 2-3 days to capture this data. A typical AI agent given 90 seconds will not do this work — it will return incomplete results or fall back to unreliable sources. Origin did the hard work once so every agent benefits.

Per-Query Cost: What AI Agents Actually Pay

An AI agent doesn't fetch everything at once. It asks specific questions. Here's the real per-query cost:

Web search: agent must discover URL, render JavaScript, parse HTML, extract data, hope it's current. Origin: structured JSON, 2-4 seconds, full provenance chain.

Your AI Communications Strategy

Today, AI agents are the fastest-growing audience for investor data. But most IR sites were built for humans reading in browsers. AI agents need structured, discoverable, verifiable data. Here's your roadmap:

Question	Via Web Search	Via Origin	Savings
"Who is SRCE?"	10,000–50,000 tokens	~200 tokens	50–250x
"Latest stock price?"	5,000–20,000 tokens	~150 tokens	33–133x
"Key people and products?"	15,000–40,000 tokens	~800 tokens	19–50x
"Show me SEC filings"	8,000–25,000 tokens	~500 tokens	16–50x

1 Publish a .well-known/ai File

Add a single JSON file at ir.1stsource.com/.well-known/ai that tells AI where to find your data. Think of it as robots.txt for AI — instead of telling crawlers what NOT to read, it tells AI agents what TO read and where.

Time to implement: 10 minutes. One JSON file, no code changes.

Preview: Your .well-known/ai file

Copy this JSON to ir.1stsource.com/.well-known/ai

{
  "schema_version": "1.0",
  "name": "1ST SOURCE CORP \u2014 Investor Relations",
  "verified_by": "origin.rootz.global",
  "investor_relations": {
    "profile": "https://origin.rootz.global/api/company/SRCE",
    "filings": "https://origin.rootz.global/api/company/SRCE/filings",
    "quotes": "https://origin.rootz.global/api/company/SRCE/quote",
    
    "signals": "https://origin.rootz.global/api/signals?ticker=SRCE",
    "static_page": "https://origin.rootz.global/static/company/SRCE.html"
  },
  "provenance": "SEC-derived data carries an origin leaf: sha256(content + parent + timestamp), plus the EDGAR accession it came from. The leaf is our hash, not a signature from the SEC — verify by re-fetching the accession from sec.gov.",
  "contact": "discover@rootz.global"
}

This is the company stating, on its own domain, where its machine-readable investor data lives and who signed it. Any agent that looks for it finds a signed copy. Whether a given agent looks is that agent's decision, not something this file compels.

2 Structure Your Key Documents

AI agents struggle with PDFs, webcasts, and JavaScript-rendered pages. The highest-impact change: publish machine-readable versions of your most-requested content.

Document	Current Format	AI-Ready Format
Company overview	HTML (often JS-rendered)	Markdown file or FAQ JSON — AI reads these natively
Earnings transcripts	Not available	Markdown + JSON with speaker tags and key metrics
Business description	Buried in 10-K PDF	Standalone MD file updated quarterly
FAQ	HTML accordion (often invisible to AI)	JSON-LD FAQ schema — search engines already support this
Press releases	HTML (varies by platform)	Structured with date, type, headline, summary fields

Why Markdown? Every major AI model reads Markdown natively. It's the universal language of AI communication. A business-description.md on your IR site is instantly consumable by Claude, GPT, Gemini, Grok — no parsing needed.

3 Anchor Your Origin IR for AI Program

AI agents are already citing your company data. The question is whether that data has a verifiable chain back to you. Origin anchoring binds your investor data to your corporate identity — so every fact carries proof of where it came from.

DNS TXT record — proves you control the IR domain
DKIM anchor — links your AI data to the same RSA key that signs your corporate email
Origin chain — every fact carries a cryptographic leaf back to its source

Data with origin is more trustworthy than data without origin. When an AI reads your anchored data, it knows the chain is real — and it carries that chain forward to everyone who reads its output.

Join our IR for AI program — we handle the setup.

4 Monitor Your AI Presence IR for AI Program

Once your data is anchored with origin, you need to see who's reading it. Program members get:

Which AI agents query your data (Claude, GPT, Gemini, Grok, institutional bots)
What topics they ask about (revenue, guidance, competitive positioning)
How you compare to peer companies
Monthly trend reports delivered to your IR team

No other service provides AI traffic analytics for investor relations. This data doesn't exist anywhere else.

Join our IR for AI program

5 Continuous AI-Readiness IR for AI Program

Program members get guaranteed scanning, capture, and origin anchoring:

Daily IR site monitoring — we detect new content within hours
Auto-capture of earnings transcripts during replay windows
SEC filing alerts — new 8-K or 10-K processed same day
Quarterly AI readiness review with your IR team