Inside Ten8: how our AI Coworker handles a routine load

When a load drops into a brokerage's TMS, the clock starts. The race to cover it is not just about price — it is about the dozens of small decisions an operator makes between "load posted" and "carrier confirmed." Ten8's AI Coworkers handle the routine version of that sequence, and hand the rest back to a human operator with context.

This piece walks through what that flow actually looks like, end to end. It is anonymized but drawn from the patterns we run today at clients like Fura Freight. We are deliberately honest about where the AI escalates instead of pretending it is fully autonomous — because that is the part most "AI broker" pitches gloss over and it is the part that determines whether a deployment compounds.

The trigger: a load lands

A 53' dry van load enters the TMS — Dallas to Memphis, pickup tomorrow, drop the day after, 22 pallets, no special equipment. Standard freight on a high-frequency lane.

Ten8 picks it up via webhook in under a second. No email scraping, no manual entry — the integration writes both ways with whichever TMS the brokerage already runs.

Step 1: Carrier scoring

Before anyone gets a call, Ten8 ranks the brokerage's carrier network for this specific lane. The scoring weighs:

• Lane match — how often this carrier runs Dallas–Memphis or adjacent corridors
• Equipment fit — dry van, 53', no reefer
• Recent performance — on-time pickups, missed appointments, claims history
• Price posture — does this carrier typically negotiate up sharply, or accept first offer
• Capacity signal — when did they last accept a load, and where

The top carriers get queued for outreach. The rest get skipped on this pass — there is no point burning calls on carriers a thousand miles from the lane.

Step 2: Outreach in parallel

Ten8 dials the top carriers in parallel and emails the next tier simultaneously. The voice agent opens with the same kind of casual line a working operator would use:

"Hey, this is Sam with [brokerage]. Got a Dallas to Memphis tomorrow, dry van, 22 pallets — wondering if you have a truck in the area?"

Most calls end inside 90 seconds — either the carrier does not have capacity, or they want details by email and the AI sends them. The productive conversations are the ones where the carrier has a truck and wants to talk rate.

Step 3: Negotiation inside the lane parameters

The brokerage sets a floor and a ceiling for the lane during onboarding. The voice agent negotiates inside those parameters and nowhere else.

If the carrier counters above the ceiling, Ten8 thanks them, says we will keep them in mind on higher-rate freight, and ends cleanly. No bluffing, no chasing.

If the counter is inside the band, Ten8 holds a multi-turn negotiation against the brokerage's playbook. Two to four turns is typical. The agent does not get tired, does not accept the first offer to be done with the call, and does not deviate from the parameters.

This is the part where the AI consistently captures margin a tired operator at 5 p.m. would have left on the table. At Fura, one documented case ran a load $70 below what a human had moved the same lane for — turning a 13% margin into a 23% margin. (Full case study: ten8.ai/case-study/fura.) That is one documented load, not a portfolio average — but it is the kind of leakage that disappears when every negotiation runs to the same playbook.

Step 4: MC verification and booking handoff

Once a rate is agreed, Ten8 runs the MC verification flow. Authority check, insurance currency, safety score, banking and contact consistency against historical norms. Anything anomalous flags for compliance review — that handoff stays human because the consequences of a missed fraud signal are real.

For clean MCs, the AI proceeds to generate the rate confirmation in the brokerage's template, send for signature, and write the booking back to the TMS as covered.

Step 5: Internal notification

At Fura, this final step happens inside Microsoft Teams. Ten8 posts the booking confirmation in the general channel — "Carrier X booked Dallas–Memphis at $Y, MC verified" — so the broader operations team knows what has happened without anyone having to message anyone else.

That detail sounds small. It is one of the changes operators bring up most in week two.

When the routine ends — the human handoff

Most of what we have described above is the routine path. Real freight has edges, and the part that matters most is what happens when the AI hits one.

Ten8 escalates to a human operator on:

• Counters that fall outside the lane band
• Carriers with rate posture or contact patterns that diverge sharply from history
• Loads where the customer changes terms mid-flight
• Anything the voice agent does not have a confident answer for
• Carriers who explicitly ask for a human

The handoff is not a dump-to-queue. The AI summarizes the context — what was negotiated, what failed, what the carrier wants — and routes the load to the right operator. The operator picks up where the AI left off without rebuilding the situation from scratch.

This is the part of the product that gets understated. The AI is not "fully autonomous." The orchestration around the handoff is the thing that makes the deployment work at scale. A vendor that cannot show you a clean handoff is selling you a demo, not a workflow.

What the operator sees

The operator who used to spend most of an hour on a load like this sees a single notification:

Dallas → Memphis covered. Carrier: [name]. Rate: $X. Margin: 14.2%. Rate con sent. MC verified.

If anything is off — a carrier asked for a longer dwell window, the consignee changed the appointment, the rate is uncomfortable — the load arrives in the operator's queue with a 30-second context summary and the recording, not a fresh blank.

Why this matters

The math on a mid-size brokerage doing meaningful load volume looks like this: most of an operator's day goes to repetitive communication — outbound to carriers who do not pick up, inbound capacity inquiries, MC checks, status updates. The actual brokering work — strategy, relationships, the loads that require judgment — is the part squeezed at the edges.

Ten8 inverts that ratio. The AI Coworker runs the routine path. The operator runs the work that actually requires a person. Headcount stays roughly flat while volume per operator climbs.

We are not replacing operators. We are giving them back the part of the job they took the job for.

What is next

We are rolling out tighter MS Teams workflows for clients who run on Teams the way Fura does — fewer notifications, more inline actions, less context switching. And we are expanding the cold-call lane-build workflow into more equipment types beyond dry van.

If you want to see the flow live on your own freight, book a demo. Two-week onboarding, first results inside the first month, outcome-based pricing. You pay when the AI delivers a result, not for a seat or a token.