AI-powered CX SaaS: the secrets of enterprise adoption with Pierce Buckley @babelforce

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In episode #30 of season 5, Anna Nadeina talks with Pierce, CEO & Co-founder of babelforce, a no-code platform for building and automating customer experience workflows, primarily focused on contact centers.

AI today feels brand new, but as Pierce reminded me, many of the foundational technologies (speech‑to‑text, text‑to‑speech, early voice assistants) have been in development for decades. What changed recently is scale and accessibility: models and tooling exploded in capability, and cloud economics made experiments cheap and fast.

That shift forced enterprises to stop being complacent about their systems. AI projects quickly expose long‑ignored issues: fragmented systems, dirty data, and orchestration gaps. Pierce summed this up with a memorable visual — an angel riding an escalator labeled “AI” that collapses into a pit labeled “data.”

“As soon as you begin an AI project the thing you come up against is — oh my god, all those things we’ve tried to ignore for the last 10 years: integration, data quality, orchestration.” — Pierce Buckley

Challenges and realities of AI implementation

Enterprise AI isn’t a simple headcount reduction lever. Two core realities Pierce highlighted:

• Automation rarely eliminates headcount at the expected scale. In many contact centers, the number of customer interactions continues to rise — Pierce referenced projections of a multi‑fold increase in touchpoints over the next several years — so agent minutes keep growing even after automation waves.
• ROI is achievable where there are routine, repeatable tasks. Replacing highly repetitive work (especially with outsourced agents billed variably) can yield quick, measurable savings; more complex cases, however, still need humans or higher skill levels from remaining staff.

Example: Pierce spoke with a large insurer running 78 AI projects. That level of experimentation is common in mature organizations — but many projects fall short of ROI because they don’t address the integration and data plumbing required to make AI useful in production.

What babelforce actually does: the value proposition

Babelforce is a no‑code/low‑code platform that focuses on voice and contact center automation. Its sweet spot is not reinventing language models, but stitching together the pieces enterprises already have — multiple CRMs, ticketing systems, AI services and voice platforms — into coherent automated customer experiences.

Pierce described the platform’s superpower as rapid data integration and orchestration for voice channels. In short: we make hard enterprise problems easier, not by promising magic, but by enabling teams to assemble “Lego blocks” of AI, telephony, and backend systems without bespoke coding for every use case.

Machine learning vs automation

While machine learning and modern LLMs are part of the stack (and getting better all the time), most of the immediate value in contact centers comes from automation and process alignment. Pierce estimated that much of the machine learning required — speech and text models, intent classification, response generation — can be sourced from general models and tuned, while the heavy work remains in integrating these models into business processes and multiple systems.

Data and integration: the hidden work

Enterprises commonly run 10–20 systems to support CX. AI projects demand frequent, accurate data lookups and cleaning. The reality is that before any LLM can be effective on a voice or chat interaction, you need:

• Reliable identity and customer context lookups
• Clean, consistently mapped data across systems
• Orchestration that switches between AI automation and human agents smoothly

That’s where a platform like babelforce pays off: reducing implementation time and complexity so enterprises can realize value faster.

From bootstrapping to product-market fit: babelforce’s journey

Pierce shared how babelforce began: a long bootstrapped build, three co‑founders and weekend coding sessions around the kitchen table. Key milestones:

• Bootstrapped for ~5 years while building a complex integration and automation platform.
• First funding round in 2019; growth accelerated thereafter.
• First ML models shipped in 2018 (smaller neural nets), and later adoption of LLM‑style components as they matured.
• Company size today: ~35 people — small, talent‑dense, enterprise‑focused.

Pierce reflected that bootstrapping was the right move early on, but admitted they waited a bit too long to take institutional capital — a nuance worth noting for founders targeting enterprise sales channels where scaling the go‑to‑market engine is expensive.

Enterprise sales, marketing, and events: what actually works

Babelforce’s growth relies on classic enterprise motion: relationship selling, long sales cycles (12–24 months of nurturing), and events. A few tactical takeaways Pierce shared:

• LinkedIn is surprisingly powerful for maintaining visibility in enterprise buy cycles — far more effective than email newsletters as an ongoing touchpoint.
• Outreach still matters, but it’s research intensive; cold calls only succeed at the end of a long funnel.
• Events require heavy investment and precision: expect 8–12 weeks of pre‑event planning, a packed schedule of prebooked meetings, professional video/photography and a long tail of post‑event content.
• Attribution is hard. Big events cost a lot and ROI is messy to measure — but the content and relationships you generate can feed your funnel for months or years.

“If you’re going to spend that much on an event, leave nothing to chance.” — Pierce Buckley

Zendesk integration: why it matters

Babelforce recently announced an important integration with Zendesk. Why this is significant:

• Zendesk is a market leader in ticketing and case management; many enterprises use it as their CRM/ticketing backbone.
• Zendesk has invested heavily in AI (including LLM‑based capabilities), but lacks a native voice channel. Babelforce plugs that gap, enabling a full stack for voice + chat + email automation using the same AI investments.
• The integration lets enterprises reuse AI components they’ve already committed to, reducing duplication of spend and simplifying the operational footprint of AI across channels.

The integration launched in late March as a beta and reflects a pragmatic, vendor‑agnostic approach: plug into the AI and tooling enterprises already have, or provide options when customers prefer babelforce‑managed AI.

Biggest win, biggest failure, and founder hacks

Pierce’s top win: a strong, multi‑year go‑to‑market relationship with Zendesk that positions babelforce competitively in the Contact Center as a Service (CCaaS) market.

Biggest misstep: waiting too long to raise institutional capital. Bootstrapping was valuable, but for enterprise, there’s a tipping point where external capital is needed to scale sales and operations effectively.

A founder hack worth repeating

Pierce’s advice to other founders is practical and humane: prioritize your physical and mental health early. He calls it high maintenance in a positive sense — regular exercise, mental health practices, and clearing your head so you can make better decisions under pressure. It’s not optional when responsibilities scale.

“Taking care of your own health and mental health is the most important thing. You need to be at your best.” — Pierce Buckley