Fragmented tech stacks, data silos, and reps who won't fill in the CRM are problems as old as RevOps itself. But what if a single AI-native platform could collapse 14 tools into one, auto-populate your sales framework fields from meeting transcripts, and let any operator build agentic workflows in an afternoon without a single ticket to IT?
In a recent RevOps Co-op demo session, David Winslow, VP of RevOps at Aurasell, and Nic Acton, Founding Forward Engineer at Aurasell, walked the community through a live product demo of the Aurasell platform. Moderated by Aliza Kogan, the session covered how Aurasell approaches tool consolidation, AI-driven data hygiene, seller focus, and agentic workflow automation with plenty of live Q&A from an engaged operator audience.
If you've sat in a RevOps role for more than a year, you've lived this story: new ask comes in, new tool gets evaluated, new integration gets built, new break-fix ticket gets filed. Multiply that by a decade and you get the modern GTM stack: a sprawling set of point solutions that technically integrate but functionally fragment.
Winslow framed this as one of Aurasell's founding tensions.
"You tend to be focused so much on infrastructure and every year there tends to be new asks for new insight, new clarity, new tooling, and it's a lot on the team. It's a lot of investment. It's a lot of time." — David Winslow
The more insidious problem, he argued, isn't the cost or the maintenance burden. It's what all those integrations fail to capture. An hour-long sales call gets summarized into whatever your CRM's field schema could accommodate fifteen years ago. A champion's shift in sentiment across three meetings never surfaces in any report. The richness disappears.
This is a challenge that maps directly to what RevOps leaders increasingly face when trying to build an AI-ready revenue stack. The data that AI needs to be useful simply isn't getting captured in a form that AI can work with.
Aurasell's answer is an AI-native configure-price-quote (CPQ) and go-to-market platform — built from scratch over 16 months before general availability — that positions itself as a replacement for as many as 14 tools: CRM, meeting recorder, dialer, sequencing, forecasting, CPQ, and more.
The first thing Winslow demonstrated was what he calls "unified context": a single timeline view for every account, contact, and opportunity that aggregates signals from email, calendar, call recordings, third-party web visits, and more.
In the live demo (using a fictional company called "Ninja One"), every touchpoint appeared in a single scrollable timeline: emails with signal tags, calls with participant role inference, web visits, and meeting summaries with extracted next steps. Switching between the account, contact, and opportunity level kept the same presentation consistent — so a new rep ramping on an account can read three months of history without hunting across four tools.
The meeting recorder output was a highlight. Beyond the transcript, Aurasell auto-generates a summary of pain points raised, assigns inferred roles to participants (champion, economic buyer, coach, influencer), surfaces interests, and creates follow-up tasks all without rep input.
"If I'm an executive coming in or I'm a sales leader coming in to an opportunity, all it takes for me is five minutes and what used to take more than an hour of build out to see what the key risks are and on a deal who's engaged in the past." — David Winslow
For RevOps teams that have spent years trying to get reps to log call notes and update opportunity fields, this reframes the problem entirely. The system captures the signal; the rep doesn't have to. This aligns with a broader argument in the RevOps community that reps cannot be the data engine behind the CRM and that data quality depends on removing that dependency.
One of the session's more technically detailed segments covered how Aurasell handles sales framework scoring and why it matters for RevOps leaders trying to enforce methodology at scale.
Aurasell supports MEDDIC, MEDDPICC, BANT, Three Whys, and other frameworks out of the box. Rather than asking reps to manually populate MEDDIC fields after a call, the platform listens to conversations and emails and auto-populates fields based on signal definitions that RevOps configures in settings.
Winslow demonstrated this live: each MEDDPICC field showed an AI-generated fill, a quality score (out of 10), and coaching suggestions for what the rep should do next to improve the score.
"For those of you that have been in heavy MEDDIC shops or heavy sales framework shops, sometimes you're not getting access all the time to your second line manager, or if you're looking to get better, you can use the tuning and all the insights that you get from things like all of this listening and tagging and coaching, just to tune your deals and get better." — David Winslow
The signal configuration in settings is straightforward: you define what a field means (for example, "Why Buy Anything" = mentions of saving time, making money, or risk), give the AI examples, turn it on, and it scores against that definition across every call and email. This is the kind of automation that transforms CRM data quality from a rep-compliance problem into a systems architecture decision.
The platform also supports stage-gating at the field level. RevOps can require specific AI-filled criteria to be met before a deal can advance to the next stage, embedding deal quality standards into the workflow rather than hoping reps remember.
Beyond data capture, Aurasell surfaces prioritization signals to help sellers focus on the right accounts and contacts at the right time.
ICP match scoring is fully configurable: RevOps defines firmographic criteria (employee count, revenue, region, industry), adds technographic filters (complementary products, existing tooling), and Aurasell scores every account in the database accordingly. Multiple ICPs can coexist — enterprise and mid-market, for example — each with its own scoring logic.
At the contact level, Aurasell generates a propensity-to-engage score based on buyer persona, recent signal activity, and demographic data. It also surfaces the reasoning behind the score alongside identified risks. This connects directly to the ICP refinement challenges that RevOps teams wrestle with constantly: knowing which accounts to work is only useful if sellers can act on that knowledge without having to reconstruct the logic from scratch.
One of the more distinctive features Winslow demonstrated was AI columns: custom, natural-language queries that run against the full account database and return scored results. In the demo, he typed: "Who is likely to attend RSA 2026? Cybersecurity company." Aurasell searched across accounts, cross-referenced firmographic data, compliance signals, and industry fit, and returned a ranked list with reasoning. That list could then be exported to a pre-built cybersecurity/RSA conference outreach sequence in a few clicks.
"Whether you're boothing, whether you have a presence, whether you're trying to target cybersecurity companies, you now have a way to then filter list. And you can run a sequence against that." — David Winslow
The session also introduced Ask Aurasell, a natural-language query interface that positions the platform not just as a system of record but as an analytical thought partner for GTM strategy.
Winslow demonstrated a prompt asking the system to identify industries beyond Aurasell's current ICP worth considering. The system searched across closed-won history, open pipeline, engagement signaling, and account database composition and returned three industry recommendations (financial services, manufacturing/aerospace, real estate) with explanations of each.
For RevOps leaders who spend time preparing business reviews, pipeline analysis, or ICP refinement exercises, this represents a different kind of leverage. Rather than pulling reports from multiple systems and synthesizing in a spreadsheet, the analysis happens in-platform against a unified dataset. This mirrors the case for thinking of AI as a revenue operations data layer rather than a bolt-on feature. The insight is only as good as the data context feeding it.
"I love that ability from Ask Aurasell that it can search across all and it can really be a thought partner, whether that's ideas on your weekly prospecting or something that you just feel you need to focus on from a green shoots or growth perspective." — David Winslow
The final segment of the demo shifted to Nic Acton, who walked through Aurasell's agentic workflow builder and made a case that operators no longer need to wait on engineering to automate complex GTM processes.
Acton demonstrated a Slack customer issue monitor workflow, then walked through the agent builder conversation that produced it. The key insight: rather than requiring detailed upfront prompt engineering, the agent builder conducts a structured conversation with the user — asking clarifying questions about timing, validation logic, and channel preferences — and generates the workflow design from those answers.
"A lot of people look at these agentic solutions and think, 'Oh, I must have to be very good at prompt engineering and have to give it all this info up front.' With our agent builder, we're finding that you really don't need to come at this with like a writer's block perspective. You can just jump in and say, I have a problem that I need to solve." — Nic Acton
The builder also handles integrations conversationally. When Acton mentioned that the fictional company also used Microsoft Teams with customers in addition to Slack and Gmail, which were already connected, the agent builder surfaced the OAuth connector inline and estimated setup time at ten to twenty seconds.
The step library covers the expected building blocks: create records, assign tasks, web research, AI analysis steps, and HTTP API calls for connecting to external systems. Integrations with major ERP systems, signal providers, and communication tools are built in; for edge cases, the agent builder will generate a custom connector.
Acton described a real internal use case: connecting Aurasell to a product analytics tool to automatically assess customer health, generate a detailed report, and update the contact and account record without any manual querying or BI pipeline setup.
"Something that at previous companies I've worked at would take several months and several tickets back and forth with the rev ops team — all set up in one afternoon." — Nic Acton
For operators who have spent time rebuilding a RevOps tech stack or managing integrations across fragmented systems, this is the kind of capability that reframes what RevOps can own directly without escalating every automation request through an engineering queue.
The live Q&A surfaced a handful of practical questions worth noting.
On integration with billing and fulfillment systems: Acton confirmed that Aurasell can connect with virtually any system that exposes an API or webhook, and that the agent builder will construct custom connectors for anything not yet in the built-in library. Aurasell also has a native CPQ product — including pricing AI, confidence scoring, and work toward auto-generating quotes from conversation signals — which reduces yet another integration dependency for teams currently running separate CPQ tools. For teams evaluating the operational complexity of modern quote-to-cash systems, this all-in-one positioning is worth examining closely.
On migrating from an existing CRM: Aurasell supports bidirectional sync with Salesforce and HubSpot, allowing teams to run Aurasell as a go-to-market operating system alongside their existing CRM while evaluating a full migration. Winslow noted that most customers ultimately choose to migrate data into Aurasell and adopt it fully, but the coexistence path is available.
On feature gaps versus Salesforce and HubSpot: Acton was direct on this.
"Boldly — those other platforms will have a lot of little onesie-twosie things that they've been building up for the past 20 years. From a core functionality and maturity platform — we are enterprise grade, we've been developed and designed and built by the people that built VMware and other major brands." — Nic Acton
Marketing automation was identified as an area still under development. Winslow acknowledged that HubSpot and Salesforce still play a role for teams with mature marketing automation workflows, with planned investment in that capability over coming quarters.
The session's core argument is one RevOps leaders will find familiar: the question isn't whether AI is coming to the go-to-market stack, but whether your current infrastructure is structured to let it work. For more on what it takes to get there, see the RevOps Co-op podcast on thinking of AI as a data-first discipline and the community discussion on whether to blow up your CRM entirely.
Check out our blog, join our community and subscribe to our YouTube Channel for more insights.
And be sure to check out Aurasell to learn more about their AI-native go-to-market platform.
.png)
.png)
.jpg)
