SalesTechStar Interview with Travis Rehl, CTO and Head of Product at Innovative Solutions

Travis Rehl, CTO and Head of Product at Innovative Solutions chats about the immense advantages agentic AI serves up modern sellers in this SalesTechStar interview while taking us through the key highlights of their new commercial product for pre-sales: DarcyIQ

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Hi Travis, tell us about your SaaS journey so far?

Our SaaS journey has been beautifully unexpected. We never intended to build a commercial product—DarcyIQ started as an internal solution to solve our own pre-sales bottleneck. As a Premier Tier AWS system integrator, our solution architects were drowning in proposal creation, taking weeks to deliver what customers needed in days.

When we began showcasing DarcyIQ to demonstrate our technical capabilities, something remarkable happened: customers started asking to buy the platform themselves. We realized we’d accidentally solved a universal pain point in technical consulting. With strong encouragement from our AWS partners and overwhelming market validation, we went into stealth mode to prepare for public launch.

Today, we’re onboarding new customers weekly, helping consulting firms triple their revenue by eliminating pre-sales bottlenecks. What started as solving our own problem has become a mission to transform how the entire industry approaches technical sales.

We’d love the top of mind highlights on DarcyIQ and how it’s an enabler for modern sellers?

DarcyIQ fundamentally transforms the economics of technical selling by compressing deal cycles from weeks to hours. We’ve seen partners achieve 70% faster sales cycles and handle 4x more opportunities without expanding their technical teams.

The platform delivers a number of breakthrough capabilities such as:

AI Call Coach: DarcyIQ joins your customer meetings in real-time, providing suggested questions, technical prompts, and insights that turn every team member into a seasoned expert. It’s like having your best solution architect whispering strategic guidance during every call.

Agentic Proposal Creation: After analyzing meeting transcripts and supporting documents, DarcyIQ generates complete technical proposals, architecture diagrams, and statements of work in minutes—work that previously took weeks. The quality is actually more consistent than manual creation because it learns from your best historical projects.

The result? Sales teams can pursue every qualified opportunity instead of losing deals to pre-sales bottlenecks.

What should sales teams and businesses keep in mind when automating deal flows?

The most important question isn’t “How do we automate our current process?” but rather “If we could redesign this process from scratch, what would it look like?”

Most sales processes evolved organically over years, accumulating inefficiencies that teams accept as “just how things work.” Automation gives you permission to fundamentally rethink these workflows. For example, if you could generate a technical proposal in 30 minutes instead of 3 weeks, how would that change your entire go-to-market strategy?

Smart automation creates a multiplier effect: faster proposals lead to higher win rates, which enables you to pursue more opportunities, which accelerates learning and improvement. The key is starting with your biggest bottleneck—usually the handoff between sales and technical teams—and working outward from there.

Don’t just digitize inefficiency; use automation as an opportunity to reimagine what’s possible.

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How are you seeing agentic AI empower sellers across sales functions, can you talk about some interesting ways in which modern sellers/peers are using agentic AI to scale sales processes?

Agentic AI is collapsing the traditional sales tech stack into unified, intelligent workflows. Instead of juggling 8-10 different tools, modern sellers are moving toward platforms that handle end-to-end processes autonomously.

In DarcyIQ, a single conversation with a prospect can trigger an entire cascade of automated actions:

• Research the customer’s technical environment and competitive landscape
• Provide real-time coaching during the meeting
• Generate customized technical proposals and statements of work
• Submit partner deal registrations and funding requests
• Update CRM records and trigger follow-up sequences

What’s revolutionary isn’t just the speed—it’s the intelligence. The system learns from every interaction, continuously improving its ability to qualify prospects, tailor solutions, and predict deal outcomes.

We’re seeing early adopters handle 300-400% more opportunities with the same headcount while actually improving deal quality. Some sellers are even opting to qualify and scope deals fully with the AI instead of  leveraging peers.  The AI doesn’t just make them faster; it makes them better at selling.

As sales teams and business heads start to rely more on AI to fuel different parts of a typical sales cycle, what should they keep in mind to ensure a human-machine balance?

Speed has a hidden cost: confidence. If AI handles too much of the sales process, sellers risk becoming order-takers who can’t deeply engage with customer challenges or adapt when conversations go off-script.

The sweet spot is using AI to eliminate administrative burden while amplifying human expertise. In our experience, the most successful implementations use AI to:

• Handle research and documentation so sellers focus on relationship-building
• Provide real-time insights during conversations rather than replacing them
• Generate first drafts that experts refine rather than final deliverables

The goal isn’t to remove humans from selling—it’s to ensure every human interaction adds unique value. AI should make your best salespeople superhuman, not make average salespeople obsolete.

How will the role of a typical sales structure and team evolve in future as AI in salestech and sales becomes more mainstream?

We’re moving toward a “validation-first” sales model where AI handles initial qualification and proposal generation, while humans focus on relationship management and deal orchestration.

Expect to see:

• Higher individual quotas as AI multiplies individual capacity
• Elevated skill requirements focused on strategic thinking rather than administrative tasks
• New hybrid roles combining technical validation with AI system optimization
• Compressed team structures with fewer but more specialized roles
• Deal desks evolved into AI governance centers ensuring quality and continuous improvement

The most successful sales organizations will be those that use AI to handle 4x more opportunities while maintaining the human touch that closes complex deals.

What are five thoughts on the future of salestech before we wrap up?

1. The transformation timeline is compressed. What we expected to happen over 3-5 years is happening in 12-18 months. Organizations that wait will find themselves competing against AI-powered competitors with fundamentally better economics.
2. Integration debt is the new technical debt. Disconnected sales tools will become obsolete. Start consolidating your stack now and ensure your data is AI-ready—clean, connected, and comprehensive.
3. Sales roles are bifurcating. High-touch relationship managers will become more valuable, while administrative sales tasks will be fully automated. The middle ground is disappearing.
4. Quality assurance becomes AI governance. Deal desks will need technical validators and AI engineers to continuously tune systems based on win/loss patterns. The companies that master this feedback loop will dominate their markets.
5. Quotas will double, but so will capabilities. Business expectations will fundamentally shift as AI-powered teams demonstrate what’s possible. The new baseline will be what only top performers achieve today.

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