Load tendering and carrier match that covers loads without the chase.
Rank eligible carriers, draft compliant tenders, follow up across channels, and escalate margin or service risk before a human awards the load.
Nothing is finalized until a human approves it.
Where the time and money actually go.
Teams manually search history, call carriers, repeat tenders, and trade speed against service and fraud risk under volatile capacity.
Carrier sales, planners, procurement, customer operations
Trigger to act: Tender acceptance is slowing, spot coverage costs are rising, carrier reps are overloaded, or managed transportation needs consistent procurement rules.
The result you can model before you sign.
Illustrative only: 5,000 loads/month × $8 lower average coverage cost on 15% of loads = $6,000 monthly opportunity. Validate through shadow recommendations before tender automation.
The outcome, plainly: Rank eligible carriers, draft compliant tenders, follow up across channels, and escalate margin or service risk before a human awards the load.
Inputs in. A cited, review-ready result out. Your expert decides.
A Optimization engine + approval copilot. Every material fact is grounded in an allowed source and returned with its identifier, with no invented data.
Deterministic optimization solver or constrained ranking model; the LLM explains options but does not own the objective; GPT-5.6 Terra or Claude Sonnet 4.6 for exception handling and natural-language interaction. OR-Tools or commercial solver when needed; Constraint test suite.
- Load requirements
- eligible carrier pool
- lane history
- rates
- performance
- capacity signals
AI-Native, not autonomous. Judgment stays with your people.
The machine does the work; the human’s role narrows to the one thing that matters, judgment. That constraint is what makes it safe to deploy.
A human awards the load; compliance failures, margin exceptions, high-value cargo, and nonstandard negotiation always escalate.
A scorecard, not a demo. We baseline what breaks in production.
Every deployment ships with an evaluation suite. These are the numbers we baseline before launch and monitor after.
The category is crowded. Most of it isn’t built for your workflow.
Fixed-scope, tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in from day one. A price you own, not a subscription you rent.
It plugs into the stack you already run.
No rip-and-replace. Access is scoped to the minimum data necessary, isolated per tenant, and fully logged.
Transparent by design. The build price buys the workflow and the proof.
A fixed implementation fee plus a monthly bill that scales with volume and governance. No hidden seats.
- ✓ One process / scope
- ✓ Live workflow on your data
- ✓ Baseline evaluation suite
- ✓ Measured vs. current process
- ✓ Full scope & integration
- ✓ Human-review UI & audit trail
- ✓ Write-back to your systems
- ✓ Production evals & monitoring
- ✓ Multi-facility rollout
- ✓ Advanced security & compliance
- ✓ Custom control & escalation
- ✓ Dedicated evaluation program
optimization jobs, market/external data, warehouse compute and approval workflow.
Planning assumptions, not vendor quotations. Your TMS and other platform licenses are separate and owned by you. Figures confirmed during scoping.
“His vast knowledge of technologies and a natural problem-solving mindset consistently lead us through complex challenges with clarity and confidence.”
Questions serious buyers ask.
Does the AI act on its own?
No. A human awards the load; compliance failures, margin exceptions, high-value cargo, and nonstandard negotiation always escalate. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: No autonomous carrier award; no tender to unverified carriers; no unbounded negotiation; no use of protected or collusive pricing signals..
How do you stop it inventing facts?
Every material claim is grounded in an allowed source record and returned with its source identifier. The system separates observed facts, model inference, and missing information, and routes to a human whenever confidence is low, evidence conflicts, or an adverse outcome is possible.
What does it cost to run each month?
A usage bill of roughly $1,150–9,100/month (optimization jobs, market/external data, warehouse compute and approval workflow), plus a $2,800/month managed retainer for evaluation, monitoring and maintenance. Your existing platform licenses are separate and already yours. Exact figures are confirmed during scoping.
Do we need a ChatGPT or Claude subscription?
No consumer ChatGPT or Claude subscription is required for the production workflow. The client needs an approved API/cloud billing account. Workspace seats are optional for internal prototyping and administrator access.
How is this different from Parade?
Tools like Parade, Transfix tools, DAT/Truckstop are broad platforms you adapt to. This is a fixed-scope implementation tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in, and a transparent price instead of a seat subscription.
How long until it’s live, and how do we prove it works?
This is a specialist opportunity. We baseline “Time to cover” first, then measure against that baseline. You see the scorecard before expanding scope, the evaluation suite ships with the system, not as an afterthought.
Bring your real numbers. Leave with a fixed-scope plan.
A 30-minute engineering-led working session, no slideware. You leave with a sized opportunity estimate, a fixed-scope pilot plan, and the integration & human-review path mapped.
VP of Growth at ViitorCloud · senior delivery owner confirmed before paid work