When a growing communications consultancy found their team using AI tools inconsistently, they needed more than training. They needed a strategy the whole team could own. Our half-day AI workshop and custom toolset recommendations transformed scattered experimentation into a principled practice that accelerated their work without compromising their creative standards.

The Opportunity

Open Book Communications, a communications consultancy and creative agency, was juggling multiple projects simultaneously and needed to scale quality without burning out their team. While some team members were experimenting with AI tools, there was no shared approach to maximize impact or align with the company’s mission and creative standards.

Leadership faced a critical question: “How do we embrace AI’s potential without chasing novelty or compromising the custom, people-first experience that defines our brand?” They wanted an AI toolset strategy that balanced cost, impact, and security; one that would accelerate their work while staying true to their values.

The Solution

We designed a half-day intensive that combined education, demonstration, and strategic planning tailored specifically to agency workflows.

The workshop preparation began with leadership interviews to map their end-to-end workflow and identify where time, quality, and visibility could improve. Then we brought the entire team together for a hands-on session that made AI accessible and immediately applicable.

We grounded the team in what AI can and cannot do in 2025, covering adoption trends and enterprise context to align on urgency and pragmatic potential. Then we explained the foundations (LLMs, embeddings, and agents) using plain-language visuals so non-technical teammates could participate confidently.

The core of the workshop focused on practical application. We taught a repeatable prompting framework: Clear, Contextual, Constrained, Creative, Calibrated, and demonstrated how small prompt changes lead to dramatically better outputs. Through live demos, we showed ChatGPT in action for research and briefs, Gamma for rapid slide creation, n8n for orchestrating multi-step workflows, and Sora to illustrate where emerging tools are heading. Beyond the workshop, we delivered a toolset strategy and budget mapped to the major components of their workflow that helped Open Book make the investments that would have the biggest impact for the most of their staff.


Looking Forward

The impact was immediate and cultural. Open Book procured licenses for the recommended tools and launched an AI workgroup that became a cross-functional forum where the team shares what’s working, publishes prompt recipes, and reviews experiments against ethics and brand standards.

The team now reports time savings on tasks across their workflow: research syntheses, first-draft copy, slide ideation, and meeting recaps. More importantly, they describe faster starts, more consistent quality, and better visibility into who’s using what and why. AI moved from novelty to a shared, principled practice anchored to client experience and creative excellence.

Founder Sharon Sampson captured the transformation:

Studies show that knowledge workers spend up to 20% of their time searching for information or tracking down colleagues who can help with specific tasks. For creative agencies managing multiple clients and deliverables, this friction compounds quickly. When teams gain a shared language and toolset for AI, they don’t just work faster, they work more confidently, with less second-guessing and more room for the creative work that defines their value.

Is your team stuck between scattered AI experiments and strategic adoption? Let’s talk about building an approach your whole team can own.

When a private equity-backed B2B services company faced an urgent technology upgrade with time running out on their exit timeline, they turned to our AI Sprint™ to validate whether AI could actually speed up their transformation. The result: proof that AI-assisted development could change how they approach modernization.

The Opportunity

After years of growth through acquisitions, this enterprise, serving multi-site operations across North America, had inherited a patchwork of outdated systems. Their decade-old platforms were becoming harder to maintain and slowing operations which was critical as they approached their investment exit.

The immediate challenge centered on their content management system. Teams spent countless hours manually moving content across disconnected tools from various acquisitions. The fragmented architecture prevented resource sharing between business units and blocked new features customers expected.

The company needed insight into how AI would deliver real acceleration, and they chose a content system migration as the test case.

The Solution

Our AI Sprint™ compressed months of validation work into an intensive two-week engagement period. We validated AI’s potential across three challenges:

• Data mapping validation. We demonstrated AI tools that could map content connections between old and new platforms. Our tests showed tasks requiring review of hundreds of items could be completed in hours, not weeks. The AI handled test cases with messy data, inconsistent naming, and complex relationships.

• Legacy system analysis. Their systems used outdated code unfamiliar to their current developers. Using tools like GitHub Copilot and ChatGPT, we showed how engineers could quickly decode legacy systems, identify connection points, and design bridges to modern platforms.

• Testing workflow design. We demonstrated how AI-powered quality checks could monitor data transfers, catch conflicts, and ensure accuracy, showing how to replace manual testing that consumed significant engineering time.

Looking Forward

The sprint validated that the company could complete their entire replatforming within their investment timeline, something that seemed impossible just a few months ago. The approaches we tested provide a roadmap for actual implementation.

The cultural shift proved equally valuable. Skeptical engineers became AI advocates after seeing validation results. Teams now understand how to approach problems differently with AI assistance. One engineer reflected, “Having AI in the back of my mind for these two weeks helped me utilize Copilot for many more things than I normally would. I really appreciate the documentation and the focus on how we learn from the work and what we can take away that serves as a launching point for future projects.”

Technical debt is a well-researched issue that 91% of CTOs worldwide cite as their biggest challenge. Managing it consumes about 30% of a typical IT budget annually, and developers spend 23-50% of their time working on it.

We have seen this firsthand – and we’ve been working with development teams who don’t feel they can spend the time learning new tools to reduce tech debt more quickly. But when we’ve carved out specific time for them to focus on it, and an embedded team to help show them new approaches, it unlocks a whole gear.

Are you ready to break the cycle? Let’s talk about getting your team out of maintenance mode and back to building what matters.

The Opportunity

Every day, Vertical Insure processes thousands of insurance policies across youth sports leagues, live events, and other verticals. But a key operational challenge slowed them down: when organizations didn't provide location data, their AI tools returned inconsistent results - sometimes placing the same organization 300 miles apart on consecutive queries.

“We had team members dedicating thousands of hours to manually verifying addresses,” says Brock Noland, CEO and Co-founder of Vertical Insure. “Without consistent location data, it became difficult to assess geographic risk accurately, which is critical to underwriting.”

This created several challenges:

• Time-consuming manual address lookups

• Difficulty ensuring compliance with state-level insurance regulations

• Increased complexity in evaluating exposure to region-specific risks like severe weather

The Solution

Blank Metal partnered with Vertical Insure to rebuild their location intelligence system from the ground up using OpenAI models.

Rather than simply swapping one AI tool for another, we designed a comprehensive solution that balanced accuracy with the speed demands of real-time underwriting:

Intelligent validation layers: We implemented multi-tier verification, with automated processing for high-confidence determinations and human review triggers for ambiguous cases.

Performance monitoring: Real-time accuracy tracking and drift detection ensure the system maintains reliability as it scales.

Smart caching: Verified location data is stored and reused, reducing redundant AI queries while maintaining accuracy.

"Blank Metal understood that we needed more than just better AI - we needed a complete rethinking of how we handle location data," explains Noland.

The Impact

The results had a measurable impact on Vertical Insure's operations:

• 95% location accuracy for standard organization queries, up from inconsistent results

• 85% reduction in manual location verification, freeing staff for higher-value work

• 3x faster policy issuance for location-dependent underwriting

But the impact extends beyond metrics. “This project reshaped how we think about AI's role in our business," says Noland. "Now we're actively exploring how AI can improve fraud detection, claims, and personalized risk. Blank Metal didn't just solve a problem; they helped us define what's next.”

Looking Forward

The partnership between Blank Metal and Vertical Insure demonstrates how thoughtful AI implementation can transform core business operations. By combining OpenAI's advanced models with enterprise-grade engineering, we helped Vertical Insure turn a recurring pain point into a competitive advantage.

For Vertical Insure, accurate location intelligence is just the beginning. The company is now positioned to lead the insurance industry's AI transformation, with plans to expand AI capabilities across their entire operation.

"The insurance industry is being rewritten by AI," concludes Noland. "With the foundation Blank Metal built, we're not just keeping pace - we're setting it."