Vooma vs Augment
You're evaluating Augment and Vooma. Both build AI agents that take repetitive communication work off your team. The difference is specialization and track record: Vooma is built exclusively for freight brokers and 3PLs, with agents running the full load lifecycle - Quote, Build, Cover, Schedule, Track, and POD - in production at Echo, MoLo, Arrive Logistics, Werner Enterprises, and Axle Logistics. Augment launched from stealth in March 2025 and has expanded into wholesale distribution.
Customers running Vooma report 15% higher email quote win rates, 86% of posted loads booked at Whitewater Freight, and 98% order entry automation at Zengistics. This page covers what the two platforms have actually proven - and the questions worth asking before you decide.
TL;DR
TL;DR: Augment builds Augie, an AI teammate for the order-to-cash lifecycle, strongest today in back-office document workflows. Vooma is an agentic orchestration platform - AI co-workers that run the full load lifecycle (Quote, Build, Cover, Schedule, Track, POD) in production at Enterprise brokerages and carriers from Echo, MoLo, Worldwide Express, and Werner Enterprises to a deep mid-market roster, processing 50 million emails and creating 300,000 quotes a month. Both take repetitive work off your team. The difference is proof, scope, and what happens after go-live.
Augment launched out of stealth in March 2025. Founder Harish Abbott previously co-founded Deliverr, which Shopify acquired for $2.1 billion, and the company has raised $110 million from investors including Redpoint and 8VC. Their flagship product is Augie, positioned as an "AI teammate" that takes ownership of tasks across the order-to-cash lifecycle. Based on their earliest customer wins and publicly cited results, the product is strongest in the back office: document collection, invoice processing, POD retrieval, with track and trace on the way. In February 2026 the company launched Knowledge Hub, a layer for capturing tribal knowledge and surfacing it inside workflows. Around the same time, Augment acquired Merlin and expanded into wholesale distribution.
Vooma is an agentic orchestration platform for freight brokers and 3PLs: AI co-workers covering the full lifecycle of a load - Quote, Build, Cover, Schedule, Track, and POD. The agents work everywhere your team communicates: phone, email, SMS, Slack, Teams, and scheduling portals. They collaborate agent-to-agent-to-human on one shared data layer, so what an agent learns in one workflow shows up in the others - a bid captured in Cover informs the rate Quote offers on that lane, and carrier behavior on the phone shapes who gets called on the next hard-to-cover load. The system is self-improving and deeply personalized: agents execute your best practices every time, so your people focus on relationships, exceptions, and managing agents.
The platform runs in production at brokerages large and small - Echo, Worldwide Express, MoLo, Arrive Logistics, Werner Enterprises, NFI, Axle Logistics, and MODE among the enterprise names, alongside a deep mid-market roster - processing 50 million emails and creating 300,000 quotes a month for 2,000 monthly quoting users. The results are public. Direct Traffic Solutions saw 50-60% of inbound carrier calls handled without a rep picking up, doubled carrier rep capacity without adding headcount as new shipper wins pushed more volume through the team, and increased gross profit per load moved through Vooma by 5%. Evans Transportation raised carrier reuse to 75-80% and, in their words, turned their carrier reps from "Domino's order takers" into strategic sellers. Behind the software is a deployment team of engineers and strategists with freight operating backgrounds, who codify your SOPs into the agents and keep tuning them in production.
Most buyers learn this the hard way: AI agents are not deploy-and-forget software. An agent on day one is like a new hire on day one. It knows the general shape of the job but not your customers, your lanes, your SOPs, or the fifteen exceptions your best ops person handles without thinking.
Getting from day-one competence to top-performer output takes the same thing it takes with a human: training, feedback, and someone experienced watching the work and correcting it. Which means the team doing that work matters as much as the software. If the people configuring your agents have never booked a load, they can't tell the difference between an agent that sounds fine and one that's quietly costing you margin on every negotiation.
This is where Vooma has made its biggest investment. Our deployment team is built from freight operators and engineers who were doing this work before the current wave of AI companies existed. When something's off in how an agent handles a carrier, they hear it - because they've had that call themselves. The Evans and DTS results above didn't come from software alone; they came from months of that team tuning agents against real freight.
Any vendor you evaluate should be able to answer the same question: after the software is live, who does the training, and what do they know about freight?
Comparison at a glance
| Feature | Vooma | Augment |
|---|---|---|
| Core positioning | Agentic orchestration platform - AI co-workers across the full load lifecycle, deployed and tuned by a freight-native team | AI teammate (Augie) for the order-to-cash lifecycle |
| Workflow scope | Quote, Build, Cover, Schedule, Track, POD delivery | Quote, dispatch, document collection, billing, track and trace |
| Production track record | Live at enterprise brokerages including Echo, Worldwide Express, MoLo, Arrive Logistics, Werner Enterprises, NFI, Axle Logistics, and MODE, with published customer results; 50M emails processed monthly | Launched from stealth March 2025; earliest cited results in back-office workflows |
| Outbound carrier sourcing | Cover runs autonomous outbound campaigns, negotiates against your SOPs, and A/B tests negotiation approaches | Not publicly evidenced as a current capability |
| Data flow between products | Shared data layer; Cover's carrier bid and liquidity data informs Quote's pricing | Not publicly described in detail |
| Industry focus | Logistics operations only | Logistics plus wholesale distribution (post-Merlin acquisition) |
Core positioning
Vooma
Agentic orchestration platform - AI co-workers across the full load lifecycle, deployed and tuned by a freight-native team
Augment
AI teammate (Augie) for the order-to-cash lifecycle
Workflow scope
Vooma
Quote, Build, Cover, Schedule, Track, POD delivery
Augment
Quote, dispatch, document collection, billing, track and trace
Production track record
Vooma
Live at enterprise brokerages including Echo, Worldwide Express, MoLo, Arrive Logistics, Werner Enterprises, NFI, Axle Logistics, and MODE, with published customer results; 50M emails processed monthly
Augment
Launched from stealth March 2025; earliest cited results in back-office workflows
Outbound carrier sourcing
Vooma
Cover runs autonomous outbound campaigns, negotiates against your SOPs, and A/B tests negotiation approaches
Augment
Not publicly evidenced as a current capability
Data flow between products
Vooma
Shared data layer; Cover's carrier bid and liquidity data informs Quote's pricing
Augment
Not publicly described in detail
Industry focus
Vooma
Logistics operations only
Augment
Logistics plus wholesale distribution (post-Merlin acquisition)
Vooma is built for freight and nothing else, with agents spanning quoting through delivery, a shared data layer, and named enterprise deployments with published results. Augment positions Augie as an AI teammate for order-to-cash, with its strongest track record in back-office automation and a recent expansion into wholesale distribution.
| Feature | Vooma | Augment |
|---|---|---|
| Implementation model | Dedicated deployment engineers and strategists with freight operating experience; ongoing tuning after go-live | Not publicly detailed |
| Knowledge capture | Executed automatically - SOPs and tribal knowledge run inside every agent interaction without an operator asking | Knowledge Hub (launched February 2026) surfaces answers through Q&A when an operator looks something up |
| Channels | Phone, email, SMS, Slack, Teams, and scheduling portal logins | Phone, email, Slack, SMS, Telegram, Teams, TMS, portals |
| Customer results | Published case studies with named customers and load-level metrics | Publicly cited results concentrated in document and billing workflows |
Implementation model
Vooma
Dedicated deployment engineers and strategists with freight operating experience; ongoing tuning after go-live
Augment
Not publicly detailed
Knowledge capture
Vooma
Executed automatically - SOPs and tribal knowledge run inside every agent interaction without an operator asking
Augment
Knowledge Hub (launched February 2026) surfaces answers through Q&A when an operator looks something up
Channels
Vooma
Phone, email, SMS, Slack, Teams, and scheduling portal logins
Augment
Phone, email, Slack, SMS, Telegram, Teams, TMS, portals
Customer results
Vooma
Published case studies with named customers and load-level metrics
Augment
Publicly cited results concentrated in document and billing workflows
Both platforms cover the communication channels a brokerage actually uses. The sharper differences are what happens inside them: Vooma's agents execute captured knowledge automatically on every interaction and are tuned in production by a freight-native deployment team, with results published at the load and margin level.
Then Augment deserves the look - document collection, invoice processing, and POD retrieval are where their publicly cited results live, and those workflows are real costs. But run Vooma through the same evaluation, because the back office is where some of Vooma's loudest numbers come from. Zengistics automated 98% of order entry with Vooma and reallocated 600-plus team hours a week to higher-impact work - in their president's words, "If we hadn't solved this, we wouldn't be profitable - full stop." Evans Transportation processes 90% of orders automatically and has built 75,000 loads through Vooma, annual time savings equal to more than six full-time reps. ShipNova cut load building from 20 minutes to 3, and Makt-Trans took contract-rate order entry from 5 minutes to 15 seconds. Across customers, that looks like 2-plus hours saved per person per day building loads and a 90% reduction in data-entry errors.
The difference is what the back office is connected to. Because Build runs on the same platform as Quote, Cover, Schedule, and Track, the clean data it creates isn't an endpoint - it's what the revenue-side agents run on. The order that gets built feeds the quote that gets priced, the load that gets covered, and the shipment that gets tracked. A standalone back-office tool cleans up data. An agent platform puts that data to work on the next load.
Ask for names and backgrounds, not an org chart. A vendor that's hired fast will staff your deployment with smart generalists who've never dispatched a truck. That gap shows up in month two, when the agent needs tuning and nobody on the vendor side can tell what's wrong.
The demo is the agent at its worst; it should improve every month after launch. Ask who's responsible for that improvement, how often they review production calls and emails, and what the cadence looks like six months in. "The model learns automatically" is not an answer.
Most platforms can demo a single workflow. Very few can show how those workflows connect, or where the system makes decisions versus routing to a human.
When your system negotiates with a carrier on an inbound call, ask where that rate goes. Does it inform what gets quoted to a shipper later? Does it shape who gets contacted on the next outbound campaign? Separate point tools will give you a vague answer. A platform with a real data layer will give you a specific one.
A knowledge base an operator can query is useful. Knowledge that runs automatically inside every carrier call and customer email is a different thing. Ask to see how a specific customer SOP changes agent behavior in production, and how you verify it applies to every relevant interaction.
Inbound carrier handling is table stakes today. Outbound is harder and significantly more valuable. If a vendor says they're working on it, factor that into your timeline.
A strong answer ties directly to revenue per operator or loads per operator, with customers on the record. Tasks automated is a vanity metric. Loads handled per person proves whether you can grow without adding headcount.
Augment is a well-funded company with real customers, and if your highest-priority problem is back-office automation - document collection, invoicing, POD retrieval - they have publicly cited results there worth evaluating.
If you're looking at the revenue side of the operation - quoting, covering, scheduling, tracking - the standard should be proof. Vooma's agents are live at enterprise brokerages like MoLo, Echo, Axle Logistics, and WWEX, the customer results are published at the load and margin level, and behind every deployment is a team of freight people training the agents the way you'd train your best new hire. Across published customers the pattern holds: 5% margin uplift on Vooma-booked loads, 15% higher email quote win rate, a 6% lift in spot win rate at Sunset Transportation, 20 to 70% of loads booked from inbound calls, and 60% less time spent scheduling. The pattern repeats across those customers: reps stop drowning in reactive work, start doing the job leadership always wanted carrier sales to be, and the business moves more freight per person.
Hold every vendor to that standard - named customers, load-level results, and a team that knows freight. The closer you look, the clearer the choice gets.
FAQ
Augment positions Augie as an AI teammate for the order-to-cash lifecycle, with its strongest publicly cited results in back-office workflows like document collection and billing. Vooma is an agentic orchestration platform whose AI co-workers run the full load lifecycle - Quote, Build, Cover, Schedule, Track, and POD - in production, with published load-level results and a freight-native deployment team tuning the agents after go-live.
Yes. Zengistics automated 98% of order entry and reallocated 600-plus hours a week, Evans Transportation processes 90% of orders automatically with 75,000 loads built, and Makt-Trans cut contract-rate order entry from 5 minutes to 15 seconds. Because Build shares a data layer with the revenue-side agents, that clean data feeds quoting, covering, and tracking on the same platform.
It is not publicly evidenced as a current capability. Vooma Cover runs autonomous outbound campaigns, negotiates against your SOPs, and A/B tests negotiation approaches, alongside handling inbound carrier calls.
Vooma processes 50 million emails and creates 300,000 quotes a month for 2,000 monthly quoting users, running in production at brokerages including Echo, Worldwide Express, MoLo, Arrive Logistics, Werner Enterprises, NFI, Axle Logistics, MODE, Sunset Transportation, and Evans.