A Q&A with Auctor CEO and co-founder, Will Sun
For system integrators, the pressure has never been higher. Clients want faster implementations, clearer accountability, and measurable outcomes. At the same time, delivery teams are being asked to do more with less, adapt to new AI capabilities, and rethink business models built for a different era.
That is the backdrop for Auctor – an AI-native system-of-action designed to give systems integrators an operational backbone that accelerates software implementations and makes each one better than the last.
Rather than trying to replace SIs, Auctor is building a platform to help them compete in the AI-era. It’s designed to reduce friction and handoffs across the service delivery lifecycle, improving traceability from sales to delivery, and helping firms make that shift toward a more AI-enabled, outcome-oriented model.
In the conversation below, Auctor’s CEO shares how the company thinks about the services-as-software category, why trust still matters in an AI-driven world, and why system integrators are at the center of AI transformation.
Q: What problem is Auctor trying to solve?
A: Today, buying and implementing enterprise software is far more complicated than it should be. Customers get pulled through a fragmented journey, from initial discovery conversations to pre-sales scoping and requirements development, to the actual implementation, testing and ongoing management of that software. The more critical the software is to enterprise operations, the more people involved – from customer buying committees to software sales and customer success teams, to the SI teams working alongside the customer. All just to realize value from something a customer has already purchased.
Our goal is to simplify that journey and remove the friction between all those handoffs. We want to make the entire experience more seamless so customers can get value from their software as quickly as possible, and SIs can deliver on outcomes faster and with less rework.
We want to be the single source of truth for the end-to-end customer journey – from the first sales conversation through implementation and post go-live support. For SIs, that matters because so much delivery risk comes from broken context. Information gets lost between pre-sales, SOW creation, requirements gathering, project execution, and customer success. We’re building the connective tissue across all of that.
Q: Why start with system integrators?
A: Today, a purpose-built, AI-native platform for system integrators does not exist. Yet consultants and SIs are the ones doing the work that turns software into business value. They sit at the center of implementation, where complexity, risk, and customer expectations all come together.
If we can help SIs work faster, with better context and more confidence, that has an immediate impact on customer value. If customers get more value, they’ll make future investments in software platforms, consume more features on the platforms, and build deeper partnerships. It’s why software vendors are so excited about what we’re building as well, and why they are investing in us.
There is this narrative in the market that services and software as we know it are dead. That couldn’t be further from the truth.
Q: Tell us about the founding story behind Auctor.
A: If you can believe it, the founding of Auctor was actually inspired by Tercera. I’ve always been an entrepreneur and I was spending a lot of time exploring the capabilities of foundation models to understand where the untapped business opportunities were. Through this research I started to dive into the world of SIs, and ran across Tercera. After speaking with the team, I then spent months talking to dozens of system integrators and ISVs across the Tercera 30 to understand how complex software implementations worked, where projects broke down, and where AI could help.
Over time, a pattern became obvious: the workflows were fragmented, the handoffs were painful, and teams were spending too much time recreating context instead of moving projects forward. We developed two features that we thought AI models could automate and tested those with SI leaders. The response was clear: if we built this well, it could fundamentally change how they delivered work.
The rest is history.
Q: What were those two use cases?
A: The first was traceability. Could we give SIs the ability to track every artifact back to its origin? For example, a user story created months into a project can be traced back to the original requirement, the statement of work, and even the pre-sales conversation. That matters enormously for SIs because delivery teams are constantly inheriting decisions made earlier in the cycle. When context is preserved, teams can move faster and with less risk.
The second was building a system-of-action that could take you from the first call through requirements, project plans, SOWs, and ultimately delivery.
Q: What do you mean by a system of action? What does that mean for SIs?
A: Most traditional enterprise software was designed to be a system-of record or system-of-work. A platform that holds data or facilitates work, but doesn’t proactively help teams move work forward.
A system-of-action actually uses AI to do something with the data that is stored in the system, while still preserving the traceability, observability and governance that is important in these systems.
For SIs, that is critical. You need speed, but you also need trust. Delivery leaders need to understand what the system is doing, why it is doing it, and whether it aligns with what the client expects. That balance between action and accountability is where we think the market is headed.
Q: How are Auctor’s AI agents different from traditional automation?
A: We apply the frontier models in a way that is purpose-built for SI workflows. We are constantly tuning our system for how these LLMs are evolving (which is fast), and are working with hundreds of consultants every day to know what works and what doesn’t. For SIs, that means they can adopt new AI capabilities without taking on all the burden of building, maintaining, and governing those capabilities themselves.
Q: Why wouldn’t SIs just build this on their own?
A: Because staying ahead on AI is hard. The models change constantly, and systems can become outdated every few weeks. It requires a ridiculous amount of time and resources to keep these systems at the forefront of what’s possible, not to mention the security, governance and enterprise readiness factors. It takes a lot to keep these systems reliable and trustworthy for the delivery teams that are staking their reputation on it. Most SIs don’t want to divert resources into chasing the AI stack itself, they want to use it as a building block so they can innovate and stay focused on client value. That is the role we play.
Q: How does Auctor help SIs move toward fixed-fee or new pricing models?
A: First, the platform gives them more confidence in delivery. Teams can work faster, maintain better alignment with clients, and reduce the risk of scope drift or execution surprises. For firms looking to deliver fixed-fee projects with a level of certainty and achieve the required margin on the work, this is important.
Second, it enables firms to rethink staffing models and get more leverage from the team they have. We’ve seen examples where one person can cover work that previously required several roles because the platform helps carry context across project management, solution design, and business analysis tasks. For firms trying to move toward fixed-fee or outcome-based pricing, that kind of leverage is incredibly important.
Q: What excites you most about scaling Auctor?
A: The chance to help modernize an industry that has been overdue for change for a long time.
This is a positive disruption story for system integrators. If we do this right, there will be less waste in the system and greater value delivered. Customers will be happier, partners will see stronger adoption and expansion. That is what excites me most: building something that improves the experience for everyone involved, starting with the firms responsible for making transformation real.