Six months ago, we announced our $26M Series A. Today, we announced a $42M Series B led by Insight Partners, with continued support from Theory Ventures, Construct Capital, Gradient Ventures and 10VC.

We’re also introducing a new look and simplifying our name. BackOps AI is now just BackOps.

A lot has changed in six months. We’ve grown the team, expanded with some of the largest companies that make and move physical goods, and seen BackOps take on increasingly complex and critical parts of their operations. More importantly, we’ve learned a lot about what BackOps can become.

The problem we started with

When we started BackOps, we saw an enormous amount of critical work happening between the systems companies had spent years implementing. Companies had invested heavily in ERPs, WMSs, TMSs, CRMs and countless other systems, while also operating across carrier portals, supplier systems, customer portals, email and spreadsheets.

Yet people were still the connective tissue between all of them.

They gathered context from multiple places, figured out what happened, applied rules and experience to decide what needed to happen next, took action across systems, coordinated with internal teams and outside parties, and followed the work until it was actually complete.

The specific process might differ from one company to another, but the underlying problem was remarkably consistent: something needs to happen, the information required is fragmented, multiple systems or people are involved, and someone has to determine the right next step and carry the work through to the outcome.

We call the distance between identifying what needs to happen and actually achieving that outcome the Resolution Gap.

For decades, people have closed that gap manually. We believed AI could fundamentally change that.

What we’ve learned

AI can understand an email or document, gather context from multiple sources, communicate with people, reason through an exception and take action. That means we can begin automating work that historically couldn’t be reduced to a simple set of deterministic steps.

But having a capable model isn’t enough.

Real-world operations are messy. Requirements differ by customer, product, order and outside party. Processes cross organizational boundaries. Information is missing. Exceptions happen. Systems and portals change. And the documented SOP often doesn’t capture what an experienced operator actually knows.

Reliable execution requires understanding what information matters, what evidence is required, what actions are permitted, when approval is necessary, when something should be escalated and what outcome you’re actually trying to achieve. Then you have to keep the process working as everything around it changes.

That’s why we stopped thinking about BackOps as simply automating tasks. The opportunity is resolution.

Since our Series A, we’ve seen some incredible examples of what this looks like at scale.

One customer has now processed more than 500,000 claims through BackOps. Monthly volume grew 150x without additional hiring, while automated resolution improved from 87% at launch to 99% today.

At another customer, a billing process spanning 13 locations required an estimated 11,000 staff hours annually. The business was preparing to hire five billing specialists and a supervisor to support its growth. BackOps reduced the average billing cycle from approximately 28 hours to 14 minutes.

The immediate value is clear. Teams can absorb significantly more volume without adding headcount at the same rate, work gets completed faster, customers receive more consistent service and recoverable value doesn’t get left behind.

But what has become increasingly clear to us over the last six months is that the longer-term opportunity is much bigger.

When the work becomes intelligence

When an experienced operator resolves an issue today, they gather context, make decisions, take action and ultimately reach an outcome. The transaction gets recorded, but much of the knowledge behind how and why it was resolved is lost.

BackOps changes that. Every completed process creates a record of the context, decisions, actions and outcomes behind the work. As that happens across thousands and eventually millions of resolutions, patterns emerge that would otherwise be very difficult to see.

We can begin to understand where processes consistently break, which exceptions repeat, what actions lead to better outcomes and where the underlying operation can improve. That intelligence can then be applied back into the process, so more work creates more intelligence and that intelligence helps produce better outcomes.

The immediate benefit is efficiency. The longer-term benefit is that the operation itself can get better over time.

We think that distinction is important. Imagine two companies in the same industry with similar scale and similar systems. One continues relying on people to bridge those systems and carries much of its operational knowledge in inboxes, spreadsheets and individual experience. The other has BackOps sitting across those operations, building a structured understanding of how its business actually works every time something is resolved.

Over time, the second company should be able to identify problems sooner, understand why certain outcomes occur, standardize what its best operators know and apply what it learns back into future work. Instead of simply adding complexity as it grows, it has the opportunity to learn from that complexity.

That’s how we believe BackOps can move from an efficiency advantage to a real competitive advantage for our customers.

The ecosystem makes this even more interesting

Companies that make and move physical goods don’t operate independently. A large grocer, for example, may interact with thousands of manufacturers, suppliers, distributors, carriers and other partners. Each company has its own systems and processes, but the work between them is deeply connected.

Today, each party generally has a fragmented view. One system records the order, another the shipment, another what was received and another a claim, deduction or payment. Much of the communication and decision-making connecting those events happens somewhere else entirely.

As BackOps expands across an ecosystem, we have the opportunity to understand more of that complete resolution path. If BackOps operates across a large grocer and many of the companies that supply it, for example, we can increasingly understand not just one side of an exception, but what created it, how it moved between parties, how it was resolved and what ultimately produced the best outcome.

This creates another flywheel. More companies and more resolutions create more context and better resolution data. That creates better intelligence and better outcomes, which makes the platform more valuable to the companies already using it and, over time, to the broader ecosystem around them.

This is also where we believe BackOps can build a proprietary data advantage.

The physical economy already generates enormous amounts of data, but most of it describes individual transactions inside individual systems. BackOps has the opportunity to capture something different: the context surrounding an issue, the decisions made to resolve it, the actions taken across systems and companies, and the eventual outcome.

Over time, that can create a proprietary understanding of how operational problems actually get resolved in the real world.

Models will continue to get better and more widely available. But a model alone doesn’t give you years of process knowledge, resolution patterns, integrations and outcome data generated from actually doing the work. We believe that combination can become increasingly defensible for BackOps and, more importantly, increasingly valuable for our customers.

And eventually, the goal shouldn’t just be resolving the same problem faster. If we can see the same issue happening repeatedly across companies, facilities or partners, we can help identify what is causing it in the first place. That gives us the opportunity to move from resolving problems to helping customers improve the processes that create them and, over time, prevent more of those problems altogether.

A new layer for the physical economy

All of this has changed how we think about where BackOps sits in the technology stack.

The systems companies use today are incredibly important, and we aren’t trying to replace them. We’re building the layer that operates across them.

BackOps gathers context from the systems and people involved, understands what needs to happen, takes permitted actions, coordinates the work and carries it through to resolution. As more work runs through BackOps, it creates a connected picture of how work actually moves through an organization and, eventually, across the companies it operates with.

The systems underneath BackOps tell a company what exists. The resolution layer can increasingly help explain what happened, why it happened, what was done about it and what can be improved going forward.

We believe that becomes an incredibly valuable layer of enterprise infrastructure, particularly for companies that make or move physical goods.

The physical world creates a unique kind of complexity. Products get damaged, shipments arrive late, inventory moves to the wrong place, documents are missing and external parties operate on different systems and timelines. The physical world doesn’t behave like an API, which is exactly why so much of this work has historically required people.

The companies responsible for manufacturing, distributing and moving the things around us have spent decades digitizing their systems. We believe the next step is connecting the work that happens between those systems and making that work increasingly intelligent.

Why we’re becoming BackOps

That brings us back to the name.

Starting today, BackOps AI is simply BackOps.

AI is fundamental to everything we’re building, but it isn’t the outcome. Our customers don’t wake up wanting more AI. They want to improve margins, grow without adding overhead at the same rate, complete work faster, provide better service and better understand what’s happening inside their operations.

Ultimately, they want their businesses to get better as they scale.

The technology underneath BackOps will continue evolving quickly. The problem we’re solving won’t. That’s why the simpler name feels right for where we’re going.

What comes next

The $42M Series B gives us the ability to invest aggressively in the platform, expand our product and engineering teams and support the growing number of enterprises putting critical operations onto BackOps.

But what excites me most isn’t simply doing more of what we’re doing today. It’s what becomes possible as the platform evolves.

We’re building toward a world where operational work doesn’t simply get automated. Every resolution contributes to a better understanding of the business, and as BackOps expands across the companies that interact with one another, that intelligence becomes even more powerful.

The more work that runs through BackOps, the more valuable that layer should become. For our customers, we want that advantage to compound.

We’re already building the next piece of that vision, and next month we’ll introduce a new product that we’re incredibly excited about. We’ll have a lot more to share then.

For now, I’m incredibly proud of the team building this, grateful to the customers trusting us with some of their most important operations, and thankful to Insight Partners, Theory Ventures, Construct Capital, Gradient Ventures and 10VC for believing in us and in where this can go.

Six months after our Series A, it feels like we’re only beginning to understand the size of the opportunity in front of us. I’m incredibly excited for what’s next.