Atlas Freight Brokerage — Quote-to-Load Automation
A mid-market freight brokerage replaced the first two hours of every broker's day with an AI agent that parses, matches, and confirms loads automatically.
Impact
What changed.
3× loads per broker per day
Average daily loads per broker tripled inside the first 60 days post-launch. The first two hours of the day stopped being parsing and started being closing.
Time-to-confirmation: 90 → 12 minutes
Average time from inbound quote to confirmed carrier dropped from 90 minutes to 12 minutes — driven by parallel confirmation requests instead of sequential phone calls.
800 → 2,400 monthly loads, zero new hires
The brokerage scaled monthly load volume 3× without adding a single new broker. The six-figure TMS rip-and-replace quote got shelved indefinitely.
The challenge
Before
Atlas Freight Brokerage had 25 brokers, every one of them losing the first two hours of the working day to the same grind: reading inbound shipment quote emails, hand-matching them against carrier capacity in the CRM, and then phoning carriers one by one to confirm. The business was healthy but capped by friction work that didn't scale. Leadership had been quoted a six-figure rip-and-replace by a TMS vendor and wasn't convinced — they wanted their existing dispatch software kept, and a focused automation built on top of it.
- Brokers losing the first 2 hours of every day to manual quote matching
- Inbound shipment requests parsed by eye from email and PDF
- Carrier capacity matched manually against CRM records
- Confirmation calls placed one carrier at a time by phone
- Time-to-confirmation averaging 90 minutes per load
- Volume capped at ~800 monthly loads with the current headcount
- TMS vendor quoting a six-figure rip-and-replace as the only path forward
- No appetite to replace existing dispatch software — too much process embedded in it
The solution
What we built
We ran our 4-week Business Automation Package. Week one we co-decided the scope: quote-to-load matching, end to end, built on top of their existing dispatch software rather than replacing it. The agent: (1) parses inbound shipment requests directly from email — origin, destination, weight, equipment type, target rate, (2) matches against active carrier capacity in their CRM using their existing lane and rate logic, (3) auto-sends confirmation requests to the top 3 matched carriers in parallel, and (4) updates the broker dashboard live as carriers respond. Brokers stop being parsers and start being closers — they pick up at the "who do I award this load to" stage, not the data-entry stage. Friday demos, 30-day post-launch tuning.
Core workflow connections
How the system flows.
- Inbound shipment emailAI agent extracts origin, destination, equipment, rate
- Parsed requestmatched against carrier capacity in existing CRM
- Top 3 carriers selected by lane history, rate, and current capacity
- Confirmation requests sent in parallel via email + SMS
- Carrier responseslive dashboard update with status per load
- Broker takes over at award stageno data entry required
- Exceptions (no capacity / rate mismatch)routed to senior broker queue
- 30-day post-launch tuninglane logic and rate thresholds refined per broker feedback
Process
How we built it.
Inbound shipment email → AI agent extracts origin, destination, equipment, rate
Parsed request → matched against carrier capacity in existing CRM
Top 3 carriers selected by lane history, rate, and current capacity
Confirmation requests sent in parallel via email + SMS
Carrier responses → live dashboard update with status per load
Broker takes over at award stage → no data entry required
Exceptions (no capacity / rate mismatch) → routed to senior broker queue
30-day post-launch tuning → lane logic and rate thresholds refined per broker feedback
Start a project
Brokers spending hours on parsing instead of closing?
Our 4-week Business Automation Package ships one production AI workflow inside your existing dispatch software — fixed scope, weekly demos, no rip-and-replace.
No retainer lock-in · Month-to-month · Full transparency
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