Freight Quote Sla Agent
Outlook inbox with 3,000 to 4,000 emails per day. No dashboard. You cannot see which quote-worthy requests were missed, how long each quote took, which reps are fastest, or what your win rate is by urgency bucket. No way to coach new team members or measure coverage.
A web dashboard showing quote volume, time-to-quote by bucket, win rate by bucket and by rep, SLA breach count, and coverage rate. Each row links to the Outlook conversation. Teams notifications alert the team when a quote request has been waiting fifteen minutes with no reply. You can see which buckets and reps are performing and which need coaching.
Your freight team misses quotes because 3,000 emails arrive every day and no one has a dashboard.
When your SLA is five minutes and your inbox gets 3,000 to 4,000 emails daily, someone assumes another rep is handling the quote request.
You cannot see your quote volume, response time, win rate, or SLA breaches in one place.
With 3,000 emails per day, quote requests slip through because no one knows which ones are actually worth quoting.
You have no per-rep metrics to coach against or to onboard new team members.
The agent watches your Outlook inbox, flags quote-worthy requests, starts a fifteen-minute clock, and gives you the metrics you've been missing.
Define which shipments are worth quoting: geography, equipment type, weight caps, bonded or hazmat flags, and per-customer overrides. The agent applies your rules to every incoming email.
If no team member replies to a quote-worthy request within fifteen minutes, the agent posts a Teams message with the customer name, route, and a link to the email. Last line of defense against missed leads.
The agent reads reply emails to determine whether each quote was won or lost. Every dashboard row links to the Outlook conversation so nothing is hallucinated.
Time-to-quote, win rate, SLA breaches, and coverage rate broken down by urgency bucket, individual coordinator, and customer. See which buckets and reps are performing and which need coaching.
This agent reads every incoming email in your watched Outlook folders and distribution lists, extracts shipment details from the email body and any attached PDFs, and decides whether it is worth quoting using rules you define. It labels each request as live, planned-in-advance, or golden so you can measure response time and win rate separately for each bucket. If no one replies within fifteen minutes, it posts a reminder to Microsoft Teams. When a reply arrives, the agent reads it to determine whether the quote was won or lost. Every metric in the dashboard links back to the original email thread so you can always verify the data and see the full conversation.
How the agent works
The agent runs continuously in the background, monitoring your Outlook inbox and distribution lists. Here is what happens each time a quote request arrives.
The agent reads the email body and parses any attached PDFs (delivery orders, rate confirmations) to extract origin, destination, weight, pallet count, equipment type, pickup window, bonded or hazmat flags, and customer identity.
The agent runs your rules against the extracted details. Is the weight under your cap? Is the equipment type on your whitelist? Is the geography in your service area? If the sender is a known customer like Trane or ProTrans, the agent applies any customer-specific rule overrides you have set. Quote-worthy or not.
If it is quote-worthy, the agent labels it as live (urgent, customer waiting), planned-in-advance (customer comfortable with longer turnaround), or golden (perfect match for your wheelhouse). Bucket determines SLA expectations and analytics grouping.
The agent starts a timer on every quote-worthy request. If no team member replies to the email thread within fifteen minutes, the agent posts a Teams message: customer name, route, age of the request, and a link to the Outlook conversation.
When someone on your team replies to the quote request, the agent reads the reply and the customer's response to determine whether the quote was won, lost, or is still pending. Every metric in the dashboard stores the email thread ID so you can click through to verify.
Inbound quote request emails +
3,000 to 4,000 emails per day across Patrick's mailbox and watched distribution lists (Operations Columbia, ProTrans Expedite, Trane, ProTrans, and others).
PDF attachments on quote emails +
Delivery orders, rate confirmations, and other documents that carry shipment details (origin, destination, weight, equipment type, pickup window).
Reply emails indicating quote acceptance or decline +
Customer responses to quoted shipments, used to determine win or loss outcome.
User-defined rules for quote-worthiness +
Geography, equipment type, weight caps, bonded or hazmat flags, and per-customer rule overrides (e.g., for Trane, weight cap is 15K lbs instead of 10K).
Customer identity from sender domain and display name +
Matched against a configurable customer list (Trane, ProTrans, John S. James, STG Logistics, etc.) to apply per-customer rule overrides.
Classify each email as quote-worthy or not +
Extract shipment details from email body and PDF attachments. Run your rules against the details. Apply per-customer overrides if the sender is a known customer.
Label quote-worthy requests by urgency +
Assign each quote-worthy request to a bucket: live (urgent), planned-in-advance (future), or golden (perfect fit). Bucket determines SLA expectations and analytics grouping.
Start a fifteen-minute SLA timer +
Begin tracking time-to-quote from the moment the email arrives. If no team member replies within fifteen minutes, prepare a Teams notification.
Detect reply emails and determine win or loss +
Read reply emails in the same thread to identify whether the quote was won, lost, or is still pending. Store the email thread ID for dashboard deep-linking.
Aggregate metrics by bucket, rep, and customer +
Calculate time-to-quote, win rate, SLA breach count, and coverage rate. Group by urgency bucket, individual coordinator, and customer for per-rep and per-customer metrics.
Quote-worthy classification (yes or no) +
Every email is marked as quote-worthy or not based on your rules and per-customer overrides.
Urgency bucket label (live, planned, or golden) +
Quote-worthy requests are labeled by urgency so you can measure response time and win rate separately for each bucket.
Time-to-quote metric +
Elapsed time from email arrival to first reply from your team, measured overall and per bucket.
Win or loss outcome +
Each quoted shipment is marked as won, lost, or pending based on reply email analysis.
SLA breach alert +
Teams notification posted if no reply within fifteen minutes. Alert includes customer name, route, and Outlook link.
Dashboard with metrics and deep-links +
Web app showing quote volume, time-to-quote by bucket, win rate by bucket and by rep, SLA breach list, and coverage rate. Every row links to the Outlook conversation.
Per-rep performance table +
Individual coordinator metrics: quotes handled, average time-to-quote, win rate, and SLA breaches.
Coverage rate metric +
Percentage of classified-as-quote-worthy emails that your team actually quoted. Shows whether you are missing opportunities.
Is this for you?
- + Freight brokers and 3PLs with high-volume inbound quote requests - If your team receives hundreds or thousands of quote requests per day across email, load boards, and distribution lists, and you need to see response time and win rate, this agent is for you.
- + Teams that live in Outlook and Microsoft 365 - This agent integrates directly with Outlook, Microsoft Teams, and Microsoft 365 SSO. If your team uses Gmail or Slack, you would need API alternatives.
- + Operators who can define quote-worthiness rules - You need to be able to articulate your rules: geography, equipment type, weight caps, bonded or hazmat flags, and per-customer overrides. If your rules are too complex or change daily, this agent is a starting point, not a complete solution.
- + Brokers who want analytics first, automation second - This agent gives you a dashboard and SLA nudges. It does not auto-draft quote responses or book shipments in your TMS. If you need end-to-end automation, this is a foundation for future builds.
- - Teams that do not use Microsoft Outlook or Microsoft 365 - This agent requires Outlook delegate access and Microsoft Teams. If your team uses Gmail, Slack, or other tools, the integration would need to be rebuilt.
- - Brokers with highly variable or undocumented quote-worthiness rules - If your rules are intuitive and change frequently, or if different reps use different criteria, the agent will need frequent retraining. This works best when rules are explicit and stable.
- - Operations that need TMS integration or EDI tendering in the first phase - This agent monitors email and gives you metrics. It does not read or write to your TMS, and it does not handle EDI tendering. Those are future builds.
- - Teams that want auto-drafted quote responses - This agent flags requests and alerts your team. It does not draft replies or send quotes automatically. If you need that, it is a follow-up build after you have enough data to identify which quote types are safe to automate.
How pricing works
This is a custom build scoped to your freight brokerage operations. Pricing includes the initial build, deployment to a private Railway instance, and integration with your Outlook mailbox and Microsoft Teams. After launch, you pay for ongoing usage: the cost is driven by email classification volume (3,000 to 4,000 emails per day) and LLM API calls via OpenRouter.
- Initial build cost covers design, development, testing, and deployment of the agent, dashboard, and rules editor.
- Ongoing usage cost is based on email volume and LLM API calls. The agent uses a cheap lightweight model for the first-pass classification (is this a quote request?) and a more capable model for rules evaluation and win-loss detection. Exact monthly cost depends on your email volume and the LLM pricing at the time of launch.
- The dashboard and Teams notifications are included. No per-user licensing or seat fees.
- Microsoft 365 and Microsoft Teams are your existing tools. This agent integrates with them via standard APIs.
- Optional: daily summary email or Teams card at end of day can be added after launch.
How does the agent know which quote requests are worth quoting?
You define the rules. The agent extracts shipment details from every incoming email (origin, destination, weight, equipment type, pickup window, bonded or hazmat flags) and runs your rules against them. Is the weight under your cap? Is the equipment type on your whitelist? Is the geography in your service area? If the sender is a known customer like Trane or ProTrans, the agent applies any customer-specific rule overrides you have set. Every email gets a yes-or-no decision based on your criteria, not the agent's guessing.
What happens if no one replies to a quote request within 15 minutes?
The agent posts a Teams message to alert your team. The message includes the customer name, route, how long the request has been waiting, and a direct link to the Outlook conversation. It is your last line of defense against missed leads. The nudge is internal only, so customers never see it.
How does the dashboard prove that the metrics are accurate and not hallucinated?
Every row in the dashboard links directly to the original Outlook email thread. Click any metric and you can read the full conversation, verify the shipment details, and see the reply that determined whether the quote was won or lost. The email thread is the system of record, and nothing in the dashboard exists without a source email to back it up.
Can the agent handle quote requests that arrive as PDF attachments or in email bodies?
Yes to both. The agent reads the email body text and parses any attached PDFs (delivery orders, rate confirmations) to extract shipment details. Whether the customer sends a structured PDF or types the details inline, the agent extracts origin, destination, weight, equipment type, pickup window, and other key fields the same way.
What metrics does the dashboard show, and how do I use them to coach my team?
The dashboard shows quote volume, time-to-quote by urgency bucket (live, planned-in-advance, golden), win rate per bucket and per individual coordinator, SLA breach count, and coverage rate (the percentage of quote-worthy requests your team actually quoted). You can see which buckets and reps are performing and which need coaching. For example, if your live-quote win rate is 60% but your planned-in-advance rate is 40%, you know where to focus training.
Does the agent automatically send quote responses to customers?
No. The agent flags requests and alerts your team when a quote is stalling. Your team writes and sends the actual quote responses. This keeps you in control of pricing, scope, exceptions, and the customer message. If you want auto-drafted responses in the future, that is a follow-up build after you have enough data to identify which quote types are safe to automate.
What if my team uses Gmail or Slack instead of Outlook and Microsoft Teams?
This agent is built for Outlook and Microsoft Teams. If your team uses Gmail, you would need the integration rebuilt to use the Gmail API instead of Microsoft Graph. If you use Slack instead of Teams, the notification system would need to be adapted to Slack webhooks. Contact us to discuss alternatives for your email and chat tools.
How much does this cost, and what drives the ongoing expense?
Pricing includes an initial build, deployment, and integration with your Outlook mailbox and Microsoft Teams. After launch, you pay for ongoing usage based on email classification volume and LLM API calls. The agent uses a lightweight model for the first-pass classification (is this a quote request?) and a more capable model for rules evaluation and win-loss detection. Exact monthly cost depends on your email volume and LLM pricing at the time of launch. No per-user licensing or seat fees.
Similar workflow pattern: multi-source data ingestion, rule-based filtering, and operational workspace sync for qualified records.
Similar extraction and audit pattern: email inbox monitoring, PDF parsing, and dashboard outputs with deep-links to source threads.
Ready to see your quote metrics and stop missing SLAs.
Let us build this agent for your freight brokerage. We will start with a prototype using synthetic emails so you can see the dashboard and rules editor in action. Then we will integrate your real Outlook mailbox, set up your Microsoft Teams notifications, and tune the rules to match your operations.