Stop Googling. Get Real-Time Dumpster Rates with a Custom AI.
Dumpster trailer rates in California vary from $350 to $850 for a 15-yard trailer. Prices change daily based on location, provider, and landfill fees.
We built a price-tracking agent for a 15-person construction company that needed daily rates from over 30 local providers. The system checks prices every morning at 6 AM and delivers a clean report in under 5 minutes. It replaced a 90-minute manual process that started their project manager's day with tedious, repetitive work.
Getting a consistent answer is a data problem, not a search problem. Reliable pricing requires checking multiple provider websites, parsing different quote formats, and tracking the results daily. This is a classic business process that can be fully automated.
What Problem Does This Solve?
Most businesses start by manually Googling for rates and calling providers. This is slow and inconsistent. You find marketing pages, not pricing tables, and the person who answers the phone may not be the one who knows the current rates for a specific zip code.
A simple web scraper built with a library like Beautiful Soup is the next logical step, but it fails quickly. Provider websites are built with JavaScript, which basic scrapers cannot render. Site layouts change without notice, breaking the parsing logic every few weeks. Many hosting platforms also identify and block scraper IP addresses, leading to silent failures where you get no data at all.
Aggregator sites seem like a solution, but they don't provide rates. They are lead generation platforms that sell your contact information. You submit a form expecting a price list and instead get five sales calls from different vendors. This adds friction and noise instead of delivering the data you need to make a quick decision.
How Does It Work?
We start by mapping the 20-30 regional providers you actually use. For each provider's website, we determine the fastest way to get a price. This is sometimes a simple pricing page, but more often it's a multi-step quote form that requires submitting details like zip code, debris type, and trailer size.
We then build a Python agent using httpx for asynchronous requests and Playwright to interact with JavaScript-heavy quote forms. This agent runs on an AWS Lambda function, triggered by a cron job every morning at 6 AM. It cycles through your list of providers, submits a standardized request to each, and extracts the resulting price information. The entire run for 25 providers completes in under 4 minutes.
Raw data from websites is messy. A price might be listed as "From $450" or "$525 plus tax and fees." We pass this unstructured text to the Claude API with a function calling schema. This reliably converts the text into a structured JSON object with distinct fields for base price, currency, and notes. This clean data is then stored in a Supabase Postgres database.
The final, structured data is formatted into a daily report and sent via email or a Slack message. The system uses structlog for detailed logging, so if a specific provider's site fails to parse, we get an immediate alert. The entire system costs under $15 per month in AWS Lambda and Claude API fees to operate.
What Are the Key Benefits?
Get Daily Rates in 4 Minutes, Not 90
The agent runs automatically at 6 AM. Your team gets a clean report before their first coffee, saving over 7 hours of manual work every week.
Pay for Results, Not Sales Calls
A single, fixed-price build. The system costs under $15/month to run, a fraction of the cost of overpaying for a single trailer rental.
You Own The Data and The Agent
We deliver the full Python source code to your GitHub. You own the price intelligence you collect, not a third-party data aggregator.
Alerts When a Website Breaks
If a provider changes their website and the agent fails, you get an instant Slack notification with the specific error. No silent failures.
Data Feeds Your Existing Workflow
The daily report can be an email, a Slack message, or a new row in a Google Sheet. The data goes where your team already works.
What Does the Process Look Like?
Provider Discovery (Week 1)
You provide a list of your preferred rental providers and typical job site zip codes. We analyze each provider's website to map out the data extraction strategy.
Agent Development (Week 2)
We write the core Python agent that queries each site. You receive a sample output file showing the structured data extracted from the first five providers.
Deployment & Delivery (Week 3)
We deploy the agent to AWS Lambda and set up the daily schedule. We configure the output format (email, Slack) and deliver the first live report.
Monitoring & Handoff (Weeks 4-6)
We monitor the agent for two weeks to handle any provider website changes. You receive the full source code, documentation, and a runbook for maintenance.
Frequently Asked Questions
- What does a system like this cost and how long does it take?
- A typical price intelligence agent takes 2-3 weeks to build. The final cost depends on the number of data sources and their complexity. An agent for 10 simple websites is a smaller project than one for 30 sites that require navigating multi-step forms. We provide a fixed-price quote after a 30-minute discovery call.
- What happens when a provider changes their website and the agent breaks?
- The agent is designed to fail gracefully for a single source. If it cannot parse one website, it logs the error, sends a Slack alert, and continues with the rest. The runbook we provide includes instructions for a Python developer to update the parsing logic for that specific site, which usually takes less than an hour.
- How is this different from using a VA with a web scraping tool?
- A VA performs a manual task, just cheaper. They are inconsistent and cannot run at 6 AM without special arrangements. We build a production-grade software asset. It is a reliable, automated system that runs for pennies, not a delegated manual task. You also own the code and the data it gathers.
- Is scraping pricing data from websites legal?
- We are automating access to publicly available information that any customer could see by navigating the website. The agent behaves like a human user, submitting standard quote requests through public forms. We do not bypass security measures or overwhelm servers. You should consult your own legal counsel for advice specific to your situation.
- What about providers that only give quotes over the phone?
- This system cannot automate phone calls. AI voice agents are not yet reliable enough for critical business conversations about pricing. For providers without a web presence, our agent handles the 80% with websites, and your team can make a few targeted calls to the remaining holdouts, still drastically reducing the manual workload.
- What format does the final data come in?
- The standard delivery is a daily email with a simple table of providers and their rates. We can also post it to a Slack channel, add a new row to a Google Sheet, or send the raw JSON data to a webhook if you want to feed it into another system. The output is configured during the build to fit your workflow.
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