Headquartered in Grand Junction, Colorado, Trusst is the Agentic CX intelligence and automation layer built natively into your AWS Cloud.
Securely integrated with your existing systems – whether it’s your contact center, CRM, or billing platform – Trusst’s platform extracts powerful insights from every customer interaction.
But it doesn’t stop there.
These insights fuel Trusst’s advanced AI agents, which automate and enhance customer experiences across all voice or text-based communications in any language. Built to stay on-brand and continuously learn from your data, Trusst agents resolve issues faster, improve satisfaction, and adapt to your business.
Deployed entirely within your own AWS environment, Trusst keeps your data secure, compliant, and under your control—transforming every conversation into meaningful business outcomes.
Trusst Use Cases:
Energy: For a fast-growing energy client, Trusst deploys, transcribes, and immediately assesses 100% of all voice interactions in an unbiased, consistent manner generating savings of $1.2 million per annum.
Banking: Trusst deploys and integrates into the existing contact center of a financial institution, saving each of their mobile bankers ~4 hours per week, freeing up time for higher value activities with estimated productivity savings of $4.6 million per annum.
Health: Trusst integrates into a health services provider’s existing contact center, delivering accurate, real-time transcription and translation for their agents. This dramatically increased customer satisfaction and reduced the human translation service expense by $2.4 million per annum.
Telecommunications: Trusst analyses 100% of all customer interactions within seconds. In the first 6 months, sales conversion increased by 3%, equating to over $2.2 million additional revenue per annum.
Insurance: Trusst’s AI Agents are deployed as the ‘front door’ interface for an insurance provider’s customers leading to significant CX experience, efficiency improvements, and over $1.7 million in annual savings.
Learn more at: trusst.ai/impact-studies
Platform vs In-House: Choosing the Right Generative AI Strategy
By Ryan Kohler, CTO Trusst AI
Learn how choosing the right generative AI platform simplifies adoption and cuts costs while accelerating organizations on their CX transformation journeys.
Overview:
We’re entering the next era of customer experience—one where AI isn’t an overlay, but the operating model itself. Trusst is designed with this in mind. This blog explores how choosing the right generative AI foundation—one built to adapt, learn, and scale with you—is critical to unlocking value faster, more securely, and with less risk.
The Allure of In-House AI Development
AI is no longer a strategic edge—it’s foundational to how modern organizations operate. While the idea of building custom AI solutions appeals to those seeking full control, the reality is far more complex. Internal development is often slowed by competing priorities, scarce expertise, and long timelines. There’s a smarter path forward: adopting a purpose-built generative AI platform that accelerates transformation while minimizing risk—enabling teams to shift focus from building infrastructure to delivering outcomes.
The Speed Factor: A Critical Catalyst
The speed at which an enterprise can deploy AI solutions now defines its ability to adapt, compete, and scale. Traditional internal builds often face delays due to long development cycles and limited resourcing. In contrast, a generative AI platform shaped by deep domain expertise in AI and customer experience provides a faster, more adaptive path forward. These platforms aren’t just accelerators—they’re enablers of transformation, helping organizations realize the value of AI quickly, continuously, and at scale.
Experts who know what moves the dial
What sets a generative AI platform apart isn’t just speed—it’s strategic depth. The most effective platforms are designed by those who understand the inner workings of customer experience operations and the metrics that matter most: cost to serve and customer lifetime value (LTV).
This embedded expertise ensures the technology isn’t just functional, but aligned to real-world business levers. It’s this intersection of technical capability and commercial insight that enables AI to move beyond automation and deliver measurable impact across the customer lifecycle.
Flexibility that fuels Transformation
Flexibility is essential in a generative AI platform. Unlike rigid, one-size-fits-all solutions, a platform that adapts to the unique dynamics of your business ensures that technology aligns with your goals—not the other way around. This kind of adaptability is key for organizations looking to embed AI across diverse use cases, creating a foundation for continuous evolution, experimentation, and scale.
Operational Efficiency: A Strategic Consideration
Building and maintaining in-house AI infrastructure is costly—not just in capital, but in the diversion of scarce AI and CX expertise. Generative AI platforms remove that burden, allowing your teams to focus on what matters most: delivering value, not managing infrastructure. Choosing a managed solution isn’t just about efficiency—it’s about creating space to scale, experiment, and drive growth through a smarter, more agile operating model.
Key Considerations for Your AI Strategy
When choosing a generative AI solution, Consider:
- Platform-first architecture for rapid integration, scalability, and long-term adaptability.
- Alignment with real-world use cases, ensuring immediate relevance and room to expand.
- Enterprise-grade security, with full data sovereignty and protection built in.
- Transparent data access, enabling organization-wide insights and continuous learning.
- Usage-based pricing models, ensuring costs align with outcomes.
The Path Forward
Opting for a generative AI platform over in-house development isn’t just a tech decision—it’s a strategic commitment to scale, speed, and sustained impact. It’s about directing resources toward outcomes, not infrastructure—freeing teams to innovate, adapt, and serve customers with intelligence that evolves in real time.
The path to AI maturity is paved with strategic choices. Choosing a platform built for flexibility, security, and long-term value helps organizations bypass the drag of custom builds and accelerate into an AI-native future. This isn’t just a recommendation—it’s a blueprint for those leading the next wave of digital transformation. It’s how you move from surviving disruption to shaping it.