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Modern 3PLs and logistics operators are under relentless pressure to make faster decisions with cleaner data—especially when onboarding new carriers and verifying compliance across truckload and ocean. The challenge is rarely a single missing field; it’s the maze of fragmented systems and delayed intelligence that turns a straightforward “Can this carrier legally haul my load, at what price, with what risk?” into a day-long chase. One vendor gives you FMCSA status, another sells AIS-derived congestion, a third provides freight rate quotes, and a fourth fires weather alerts—but none of them correlate the events that matter along the journey of a shipment or the lifecycle of a carrier relationship.

This post shows how to use event correlation across carriers, freight quotes, fuel indexes, port congestion, and natural-disruption alerts to build automated onboarding and continuous compliance verification flows. Rather than wiring five feeds and building your own observability and retries, you can consolidate the data behind a single, developer-friendly surface. The result: fewer manual checks, faster time to acceptance decisions, and proactive risk controls that trigger before a violation or weather event derails a shipment—or worse, a customer relationship.

We’ll walk through practical steps using FreightPulse, including lookups for FMCSA and FMC carriers, live US FTL quotes, EIA fuel series, IMF PortWatch–based port congestion, and GDACS/USGS/NOAA natural-disruption alerts. Along the way, you’ll learn how to interpret the responses, correlate events, handle edge cases, and ship with operational reliability.

Why FreightPulse

If you’ve ever stitched together EIA fuel data, FMCSA carrier status, a freight quote provider, and an AIS-based congestion feed, you already know the hidden effort: mismatched schemas, missing fields, changing vendor rate limits, and brittle retry logic. FreightPulse removes the multi-vendor sprawl by consolidating this data into one cohesive REST API, with consistent response shapes and pragmatic, production-ready defaults. Here are a few practical reasons teams adopt it:

In short: what used to be five feeds, five different schemas, five different retry strategies, and five different vendor dashboards is now one cohesive API designed for developers and operators building modern supply chain systems.

Quick Start

Base URL: https://freightpulsehq.com/api/v1

All responses follow a consistent envelope: {"success": true/false, "data": {...}, "error": "..."} (when success is false). The examples below show two of the fastest calls you can make to begin validating a carrier vetting flow while also sampling market conditions for pricing.

Example 1: Retrieve national fuel prices to power a fuel-surcharge calculator or baseline your TMS’s weekly adjustments. 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/fuel-prices"

{
"success": true,
"data": {
"timestamp": "2026-07-30T12:00:00Z",
"source": "EIA (U.S. Energy Information Administration)",
"currency": "USD",
"unit": "gallon",
"data": {
"diesel": {
"national_average": 3.847,
"change_week": -0.023,
"change_percent": -0.6,
"regions": {
"east_coast": 3.912,
"midwest": 3.756,
"gulf_coast": 3.623,
"rocky_mountain": 3.891,
"west_coast": 4.456,
"california": 4.892
},
"historical": {
"30d_avg": 3.82,
"90d_avg": 3.75,
"yoy_change_percent": -8.2
}
},
"gasoline": {
"national_average": 3.156,
"historical": {
"30d_avg": 3.1,
"90d_avg": 3.05,
"yoy_change_percent": 1.1
}
}
}
}
}

Key fields and why they matter:

Example 2: Query a carrier by DOT number during onboarding, then fuse the outcome with other checks (e.g., safety, drivers on file). 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/carriers?q=54283"

{
"success": true,
"data": {
"type": "trucking",
"query": "54283",
"results": [
{
"dot_number": 54283,
"legal_name": "SWIFT TRANSPORTATION COMPANY OF ARIZONA LLC",
"status": "active",
"safety_rating": "S",
"drivers": 12883,
"address": {
"city": "Phoenix",
"state": "AZ",
"country": "US"
}
}
]
}
}

Key fields and why they matter:

Core Endpoints

1) Carrier lookups for onboarding and compliance — GET /carriers

Purpose: Verify carrier legitimacy and risk posture during onboarding, dispatch, or periodic compliance audits. FreightPulse aggregates FMCSA SAFER data for US trucking carriers and FMC NVOCC/OTI lookups for ocean. Air returns available:false to avoid false expectations.

Key parameters: 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/carriers?q=MAERSK&type=ocean"

{
"success": true,
"data": {
"type": "ocean",
"query": "MAERSK",
"results": [
{
"org_number": "123456",
"legal_name": "A.P. MØLLER–MÆRSK A/S",
"status": "active",
"category": "NVOCC/OTI",
"address": {
"city": "Copenhagen",
"state": null,
"country": "DK"
}
}
]
}
}

Field breakdown and usage:

Error handling tips:

2) Disruption intelligence for proactive risk gating — GET /disruptions

Purpose: Automate “environment-aware” checks during onboarding or dispatch by filtering for natural hazards near relevant ports or geographies. FreightPulse consolidates GDACS, USGS, and NOAA/NWS (US weather) to give a single view of cyclones, earthquakes, floods, volcanoes, droughts, wildfires, and severe weather. For ports, you can filter by proximity to catch potential impacts before they materialize in delays or safety issues.

Key parameters: 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/disruptions?port=USLAX&severity=high"

{
"success": true,
"data": {
"results": [
{
"id": "gdacs:TC:1001305",
"type": "cyclone",
"severity": "moderate",
"title": "Tropical Cyclone SAUDEL-26",
"country": "Japan",
"starts_at": "2026-08-18T12:00:00+00:00",
"source": "GDACS"
}
]
}
}

Field breakdown and usage:

Operational tips:

3) Port congestion to steer bookings and expectations — GET /port-congestion

Purpose: Provide a 7-day average of port calls relative to a 90-day baseline to understand whether port activity is depressed or elevated, approximating congestion trends. It is built from IMF PortWatch AIS data and intentionally lagged by ~6–7 days. Use it for trend-aware planning and expectation setting—not live berth wait times.

Key parameters: 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/port-congestion?port=USLAX"

{
"success": true,
"data": {
"results": [
{
"port": "Los Angeles-Long Beach",
"locode": "US LAX",
"country": "United States",
"congestion": "moderate",
"as_of": "2026-08-14",
"metrics": {
"recent_avg_portcalls_per_day": 8.7,
"baseline_avg_portcalls_per_day": 10.2,
"ratio_vs_baseline": 0.85
}
}
]
}
}

Field breakdown and usage:

4) Live truckload pricing to contextualize onboarding decisions — GET /freight-rates

Purpose: During onboarding, it’s common to benchmark a new carrier’s submitted rate against a market reference. FreightPulse integrates live US FTL quotes (via Warp) so you can quickly gauge competitiveness for a lane before you invest effort in deeper qualification.

Key parameters: 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/freight-rates?mode=trucking&origin_zip=10001&destination_zip=90210"

{
"success": true,
"data": {
"mode": "trucking",
"service": "FTL (53' dry van)",
"source": "Warp",
"price_usd": 7207.92,
"transit_days": 4,
"pickup_date": "2026-08-24",
"delivery_date": "2026-08-28"
}
}

Field breakdown and usage:

5) Fuel prices and historicals to complete the pricing stack — GET /fuel-prices and GET /historical

Purpose: Live truckload quotes answer “What is the market now?” while EIA diesel and gasoline series answer “What has the trend been, and what should our surcharge be?” FreightPulse gives you both surfaces—current aggregates and time series—for dashboards and automated pricing models.

Key parameters: 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/historical?metric=fuel_price_diesel_national&period=30d"

{
"success": true,
"data": {
"metric": "fuel_price_diesel_national",
"period": "30d",
"series": [
{ "date": "2026-07-27", "value": 5.257 },
{ "date": "2026-08-03", "value": 5.343 }
]
}
}

Field breakdown and usage:

From Data to Decisions: Event Correlation for Onboarding and Continuous Compliance

A robust onboarding or compliance pipeline coordinates multiple checks: identity (carrier lookup), market sanity (pricing), environmental risk (disruptions), and flow constraints (port congestion) with financial normalization (fuel). FreightPulse’s consistent schemas enable you to orchestrate these checks in parallel, then correlate into a single decision matrix. Here’s a reference flow:

Because all responses share a {"success", "data"} envelope, you can pipe results into a single evaluator with composable rules. For example:

End-to-End Example: Correlated Checks with Python

The following Python-like flow demonstrates correlating carriers, rates, congestion, disruptions, and fuel. It uses synchronous calls for clarity; in production, run them concurrently with retries and circuit breakers. 

import os
import requests

BASE = "https://freightpulsehq.com/api/v1"
HEADERS = {"X-API-Key": os.getenv("FP_API_KEY", "YOUR_API_KEY")}

def get_carrier(dot):
r = requests.get(f"{BASE}/carriers", headers=HEADERS, params={"q": str(dot)})
return r.json()

def get_truck_rate(origin_zip, destination_zip):
r = requests.get(f"{BASE}/freight-rates", headers=HEADERS, params={
"mode": "trucking",
"origin_zip": origin_zip,
"destination_zip": destination_zip
})
return r.json()

def get_port_congestion(locode):
r = requests.get(f"{BASE}/port-congestion", headers=HEADERS, params={"port": locode})
return r.json()

def get_disruptions_near_port(locode, severity="high"):
r = requests.get(f"{BASE}/disruptions", headers=HEADERS, params={"port": locode, "severity": severity})
return r.json()

def get_fuel_prices():
r = requests.get(f"{BASE}/fuel-prices", headers=HEADERS)
return r.json()

def evaluate(dot, origin_zip, destination_zip, origin_port):
carrier = get_carrier(dot)
rates = get_truck_rate(origin_zip, destination_zip)
congestion = get_port_congestion(origin_port)
disruptions = get_disruptions_near_port(origin_port, "high")
fuel = get_fuel_prices()

if not carrier.get("success"): return {"decision": "review", "reason": "carrier_error"}
if not rates.get("success"): return {"decision": "review", "reason": "rate_error"}
if not congestion.get("success"): return {"decision": "review", "reason": "congestion_error"}
if not disruptions.get("success"): return {"decision": "review", "reason": "disruption_error"}
if not fuel.get("success"): return {"decision": "review", "reason": "fuel_error"}

c = carrier["data"]["results"][0] if carrier["data"]["results"] else None
if not c or c.get("status") != "active":
return {"decision": "reject", "reason": "inactive_or_not_found"}

price = rates["data"].get("price_usd")
if price is None:
return {"decision": "review", "reason": "no_market_quote"}

high_disruptions = disruptions["data"].get("results", [])
if high_disruptions:
return {"decision": "hold", "reason": "high_severity_disruption_near_port"}

cong = congestion["data"]["results"][0] if congestion["data"]["results"] else None
if cong and cong.get("congestion") == "high":
return {"decision": "review", "reason": "high_congestion"}

diesel = fuel["data"]["data"]["diesel"]["national_average"]
return {"decision": "approve", "reason": "meets_criteria", "diesel_index": diesel, "market_price_usd": price}

result = evaluate(54283, "10001", "90210", "USLAX")
print(result)

In practice, you would:

JavaScript Example: Building a Frontend Vetting Panel

A simple browser-based panel can call FreightPulse endpoints server-side via a proxy or directly in Node.js. Below is a Node/Express style snippet fetching correlated insights for a vetting page. 

import express from "express";
import fetch from "node-fetch";

const app = express();
const BASE = "https://freightpulsehq.com/api/v1";
const API_KEY = process.env.FP_API_KEY || "YOUR_API_KEY";

const fp = (path, params = {}) => {
const url = new URL(path, BASE);
Object.keys(params).forEach(k => url.searchParams.append(k, params[k]));
return fetch(url.toString(), {
headers: { "X-API-Key": API_KEY }
}).then(r => r.json());
};

app.get("/api/vetting", async (req, res) => {
try {
const { dot, oz, dz, port } = req.query;
const [carrier, rates, congestion, disruptions, fuel] = await Promise.all([
fp("/carriers", { q: dot }),
fp("/freight-rates", { mode: "trucking", origin_zip: oz, destination_zip: dz }),
fp("/port-congestion", { port }),
fp("/disruptions", { port, severity: "high" }),
fp("/fuel-prices")
]);

res.json({
carrier,
rates,
congestion,
disruptions,
fuel
});
} catch (e) {
res.status(500).json({ success: false, error: "Internal error" });
}
});

app.listen(3000, () => console.log("Vetting panel running on 3000"));

Use UI affordances to show “active/inactive” carriers, current market rate anchors, congestion badges, and disruption banners. Because FreightPulse responses are harmonized, you can reuse your fetch-and-parse wrappers for any endpoint.

Operational Reliability: Retries, Backoff, Observability, and Governance

Production logistics software lives and dies by reliability. Align your FreightPulse integration with the following best practices:

These patterns help future-proof your integration as volume scales and your compliance surface grows. Because FreightPulse normalizes responses, your telemetry and dashboards remain consistent across endpoints.

Real-World Use Cases

Here are three concrete builds you can ship quickly:

Detailed Endpoint Walkthroughs with Complete JSON

A) GET /carriers — Trucking example with detailed parsing 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/carriers?q=SWIFT%20TRANSPORTATION"

{
"success": true,
"data": {
"type": "trucking",
"query": "SWIFT TRANSPORTATION",
"results": [
{
"dot_number": 54283,
"legal_name": "SWIFT TRANSPORTATION COMPANY OF ARIZONA LLC",
"status": "active",
"safety_rating": "S",
"drivers": 12883,
"address": {
"city": "Phoenix",
"state": "AZ",
"country": "US"
}
}
]
}
}

B) GET /disruptions — Filtering multiple types 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/disruptions?type=severe_weather&country=US"

{
"success": true,
"data": {
"results": [
{
"id": "nws:SW:TX-20260818-001",
"type": "severe_weather",
"severity": "high",
"title": "Excessive Heat Warning - Dallas County",
"country": "United States",
"starts_at": "2026-08-18T10:00:00Z",
"source": "NOAA/NWS"
},
{
"id": "nws:SW:FL-20260818-002",
"type": "severe_weather",
"severity": "moderate",
"title": "Tropical Storm Watch - Miami-Dade",
"country": "United States",
"starts_at": "2026-08-19T18:00:00Z",
"source": "NOAA/NWS"
}
]
}
}

C) GET /port-congestion — Query by region for comparative analysis 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/port-congestion?country=United%20States"

{
"success": true,
"data": {
"results": [
{
"port": "Los Angeles-Long Beach",
"locode": "US LAX",
"country": "United States",
"congestion": "moderate",
"as_of": "2026-08-14",
"metrics": {
"recent_avg_portcalls_per_day": 8.7,
"baseline_avg_portcalls_per_day": 10.2,
"ratio_vs_baseline": 0.85
}
},
{
"port": "Port of New York and New Jersey",
"locode": "US NYC",
"country": "United States",
"congestion": "low",
"as_of": "2026-08-14",
"metrics": {
"recent_avg_portcalls_per_day": 7.1,
"baseline_avg_portcalls_per_day": 7.3,
"ratio_vs_baseline": 0.97
}
}
]
}
}

D) GET /freight-rates — Missing parameters behavior 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/freight-rates?mode=trucking"

{
"success": true,
"data": {
"available": false,
"mode": "trucking",
"reason": "Missing required origin_zip or destination_zip"
}
}

E) GET /historical — Port congestion series 

curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/historical?metric=port_congestion:USLAX&period=90d"

{
"success": true,
"data": {
"metric": "port_congestion:USLAX",
"period": "90d",
"series": [
{ "date": "2026-06-01", "value": 0.92 },
{ "date": "2026-06-08", "value": 0.88 },
{ "date": "2026-06-15", "value": 0.86 }
]
}
}

Error Scenarios and Defensive Engineering

While FreightPulse responses are harmonized, production code still needs to plan for validation errors, timeouts, and business-level misses. Key patterns:

End-to-End cURL Session for a Typical Vetting Run

Tie everything together via command line to test your pipeline in isolation: 

# 1) Carrier identity and status
curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/carriers?q=54283"

# 2) Rate check for target lane
curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/freight-rates?mode=trucking&origin_zip=60601&destination_zip=77001"

# 3) Environment risk near relevant port
curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/disruptions?port=USLAX&severity=high"

# 4) Port trend context
curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/port-congestion?port=USLAX"

# 5) Fuel baseline for surcharge
curl -H "X-API-Key: YOUR_API_KEY" \
"https://freightpulsehq.com/api/v1/fuel-prices"

With these five calls, you can form a complete decision: legitimate and active carrier; market-aligned quote; acceptable environmental and throughput risk; and a known fuel baseline to price for margin integrity.

FAQ

How often do FreightPulse fuel prices update?

Fuel prices are sourced from the EIA and presented with national and PADD-region breakdowns. Use the timestamp and historical averages to detect changes week over week, and cache the payload in your app to minimize redundant fetches.

Can I look up ocean carriers as well as trucking carriers?

Yes. Use /carriers with type=ocean and a company name or organization number to query FMC NVOCC/OTI records. For US trucking carriers, omit type or set type=trucking and query by DOT number or legal name.

Does the port congestion data reflect real-time vessel wait times?

No. Congestion is a lagged approximation (~6–7 days) based on a 7-day average of port calls relative to a 90-day baseline. It is ideal for trend-aware planning and port selection but not a live AIS tracking substitute.

Can I filter natural-disruption alerts by proximity to a specific port?

Yes. Use /disruptions with the port parameter (LOCODE or name). Results are filtered within a set radius (typically 300 km; 100 km for US weather). Combine with severity to tailor automated gating logic.

What does the success field in responses signify?

Every response includes success. When true, data contains the payload; when false, error provides a human-readable message. This consistent shape simplifies error handling and logging across endpoints.

Conclusion + CTA

Carrier onboarding and continuous compliance don’t have to be a tangled web of point integrations and manual checks. By correlating identity (FMCSA/FMC), market benchmarks (live FTL quotes), environment signals (disruptions near ports), throughput trends (lagged congestion), and pricing baselines (EIA fuel), you can move from reactive to proactive—with machine-enforced guardrails and operator-friendly context. FreightPulse’s single, consistent API surface is the foundation for these flows.

Whether you are a 3PL automating new carrier approvals, a forwarder balancing port risk, or a shipper building a compliance-aware TMS, the path from proof-of-concept to production is straightforward. Integrate the endpoints shown here, add retries and observability, and start correlating events into decisions that your teams and customers can trust.

Build faster with unified logistics intelligence. Explore the endpoints showcased above at FreightPulse and put your onboarding and compliance verification workflows on autopilot. Ready to experiment today? Try FreightPulse for free and ship your first correlated decision flow in hours—not weeks.