Building Bridges: Meet Lelapa AI

Lelapa AI is tackling one of technology's most pressing challenges—bringing world-class language technologies to African languages. As CTO Jade explains, "We build language technologies for African languages, specifically focused on transcription and translation." With over a decade of experience deploying AI models into production "before it was cool or a good idea," she leads the engineering, research, and data functions that power Lelapa's mission.

What sets Lelapa apart? "We have specialized data creation techniques, rather than data scraping," Jade notes. "This enables us to support our customers very well." Combined with custom model architectures designed for efficient training and serving, Lelapa has built something truly unique in the language AI space.

The Breaking Point: When Success Becomes a Problem

Cold-start times were CRAZY—up to 30 minutes sometimes, which is unacceptable,

Before Cerebrium, Lelapa faced a critical infrastructure challenge that threatened their growth. While they'd solved deployment ease using Hugging Face inference endpoints, the solution came with a devastating trade-off: cold-start times that could stretch up to 30 minutes.

"Cold-start times were CRAZY—up to 30 minutes sometimes, which is unacceptable," Jade recalls. For a service promising synchronous responses to clients who need real-time transcription and translation, this was a dealbreaker. "Clients can't be waiting 20 minutes for a transcription machine turning on—for something that is meant to be solvable in a synchronous call."

The problem compounded as they scaled. Their clients' burstable loads meant sudden traffic spikes, and keeping machines hot to avoid cold starts was burning through budgets. "Our unit costs were large because of all the scale up and cool down wastage."

The Search for a Solution

Lelapa evaluated multiple options—from self-managing GPU loads via their cloud provider to platforms like RunPod and Vast AI. But each came with compromises. They needed something that could handle their technical requirements: burstable loads with synchronous responses and a large pipeline of high-latency models of varying sizes and architectures.

What convinced them to choose Cerebrium? Three factors stood out:

"The super sleek and effective developer experience—from onboarding to examples," Jade explains. But it went beyond just good documentation. "The customer support was highly, highly responsive and very keen to help. Always acting on feedback."

Finally, Cerebrium's focus made the difference. "Many serverless alternatives aren't necessarily focusing on the inference use cases. And the pay-for-what-you-use model—charging per core, per mem, per GPU—just made sense."

From Zero to Production in Five Minutes

Never expected such incredible customer service

The onboarding experience exceeded expectations. "I use it as an example to others, it's so good," Jade shares. Within the first week—actually, within the first five minutes—they achieved what had been impossible before: "Get a model running from nothing in less than 5 minutes."

The transition brought pleasant surprises. "Never expected such incredible customer service," she notes. Moving from Hugging Face's click-to-deploy to Cerebrium's platform, they integrated it seamlessly with their Concourse-based continuous deployment pipeline. The flexibility was transformative—no longer constrained to Hugging Face-compliant models, they could deploy any architecture with Docker support when needed.

The Transformation: From Bottleneck to Breakthrough

Our error rates for serving have dropped.

The impact was immediate and measurable. Cold-start times dropped from 30 minutes to manageable levels. "Significantly improved our cold-start problem," Jade confirms. While infrastructure costs increased with scale, the trade-off was worth it: "Our error rates for serving have dropped."

More importantly, Cerebrium eliminated hidden costs. "Definitely infrastructure and maintenance—time and cost!" The team could focus on what they do best: building language technologies that serve African communities, rather than wrestling with infrastructure.

Building Trust Through Partnership

They're great. Highly helpful and very responsive

For Lelapa, the relationship with Cerebrium goes beyond vendor and customer. "They're great. Highly helpful and very responsive," Jade says simply. This partnership has enabled Lelapa to maintain their momentum in bringing language equality to millions of speakers across Africa.

The simplicity of deployment, combined with the flexibility to handle their diverse model pipeline, means Lelapa can iterate faster, serve customers better, and expand their language coverage without infrastructure holding them back.

The Bottom Line

Cerebrium transformed Lelapa AI's ability to deliver on their mission. By solving the cold-start problem and providing a developer-friendly platform with exceptional support, Cerebrium enabled Lelapa to focus on what matters: breaking down language barriers and bringing world-class AI to African languages.

As more organizations recognize the importance of inclusive language technology, Lelapa is ready to scale—with infrastructure that can keep up with their ambitions.