What AVRL Is
AVRL, short for Advanced Voice Research Labs, was founded in 2017 in Austin, Texas, by Chadd Olesen and Nikolai Pereira. It started as a natural language processing company and pivoted in 2020 to focus on automating spot freight pricing for brokers. Its platform, Generation, uses decision trees, RPA, and chatbots to automate workflows across transportation and logistics, and the company describes its work more broadly as connecting disparate systems like TMS, WMS, and ERP platforms, not exclusively quoting.
AVRL has been recognized on the Inc. 5000 list in multiple years (2023, 2024, and 2025) and reports 51 to 200 employees. According to the company’s own public statements, AVRL works with more than half of the top 100 3PLs and has automated over 60 million shipments. We have not independently verified those figures.
Side by Side
| AVRL | Tabi Connect | |
| Founded | 2017 (pivoted to freight pricing in 2020) | 2023 |
| Core architecture | RPA, decision trees, chatbots | Native API where available, RPA where it isn’t |
| Primary focus | Automation infrastructure across transportation and logistics broadly | Purpose-built for the freight quoting workflow specifically |
| Spot quoting | Yes, core use case since 2020 | Yes, via QuickQuote and BulkQuote |
| RFP / bid season quoting | Not publicly detailed | Yes, via RFPQuote, same pricing logic as spot |
| Email channel | Not a publicized focus area | Yes, via EmailQuote |
| Chat-based quoting (Slack/Teams) | Not publicly offered | Yes, via ChatQuote |
| Private rate engine from own data | Not publicly detailed | Yes, via My Lane Rate |
| Human review before automation | Not publicly detailed | Yes, via Control Tower |
| AI pricing rules and AI-assisted insights | Not publicly detailed | Yes, plain English rules and natural language data queries |
| Configuration model | Decision trees and RPA, typically configured and maintained by development resources | No-code, plain English rule building, configurable directly by a pricing or ops lead |
| Reported customer base | Enterprise and large 3PL accounts | 100+ customers including 30+ of the Top 100 3PLs |
Where a row says “not publicly detailed,” that means we did not find published information confirming the capability, not that AVRL doesn’t offer it. Worth confirming directly with AVRL.
Where This Actually Matters
AVRL’s RPA and decision-tree foundation is genuinely broad, it’s built to automate more than just quoting, which is part of why it’s found traction connecting large 3PLs’ disparate systems. The tradeoff of that breadth is depth in any one workflow. Its public materials don’t detail RFP-specific tooling, a private historical rate engine, or a graduated path from manual review to full automation, the kind of quoting-specific depth that comes from building a platform around one workflow rather than automation infrastructure in general.
The other cost is ongoing, not just upfront. Decision trees and RPA typically need development resources to build and maintain, since there isn’t a true no-code or low-code interface for the team actually pricing freight to use directly. That raises the total cost of ownership beyond the subscription price, and it means a change to pricing logic runs through whoever built the automation rather than whoever’s setting the rate, which affects the ROI math more than the sticker price suggests.
If what you need is broad automation across multiple systems and you have the technical resources to configure decision trees for your specific processes, AVRL’s approach may fit. If what you need is a platform built specifically to cover every channel and workflow in freight quoting, with pricing logic, your own data, and visibility built in from the start, that’s the problem Tabi Connect was built to solve. The full breakdown of what that coverage looks like is on the Tabi Connect platform overview.
Frequently Asked Questions
What does AVRL do?
AVRL, short for Advanced Voice Research Labs, is an Austin-based automation company founded in 2017. It builds RPA and decision-tree based automation for transportation and logistics companies, including chatbots, workflow automation, and systems integration, and has focused on spot freight pricing automation since 2020.
Is AVRL only for large brokerages?
AVRL’s public case studies and reported customer base skew toward enterprise and large 3PL accounts. That doesn’t mean smaller brokerages can’t use it, but its go-to-market has been most visible at the top end of the market.
Does AVRL support RFP or bid season quoting?
AVRL’s publicly available materials focus on spot pricing automation, RPA-based integrations, and decision-tree logic. We did not find published detail on a dedicated RFP or bulk lane file quoting workflow, so this is worth confirming directly with AVRL if it matters for your evaluation.
What’s the main architectural difference between Tabi Connect and AVRL?
AVRL is built primarily around RPA and decision-tree automation. Tabi Connect uses native API integrations wherever available and RPA where it isn’t, and covers channel capture, pricing logic, RFP and spot workflows, a private rate engine, and analytics as one connected platform rather than a single automation layer.
Does AVRL require development resources to use?
AVRL’s platform is built on decision trees and RPA, which typically require development work to configure and maintain rather than a no-code interface a pricing or operations lead could use directly. That adds to the total cost of ownership beyond the subscription price and is worth factoring into an ROI comparison, alongside the subscription cost itself.
See How Tabi Connect Compares to Other Vendors
See What a Purpose-Built Quoting Platform Covers
Every channel, both spot and RFP, your own rate data, and full visibility, purpose-built for freight quoting. Book a demo to see the Tabi Connect platform in action.
