Intelligence for real progress.
Fikra API started with a simple observation: the tools to build with AI exist, but production-grade access doesn't always reach the developers shaping what comes next. We are building the inference layer so you can focus on building the product.
Infrastructure First
Built for SLAs, reserved throughput, and genuine production reliability.
Deep Optimization
Operating custom ternary weight models for maximum edge efficiency.
Economic Reality
Integrated with M-Pesa. Pricing that scales honestly with your business.
Engineering Support
When infrastructure breaks, you talk to the engineers writing the code.
"I kept watching developers hit the same wall — Stripe not supported, heavy minimums, no direct support. The tools to build AI exist. The production-grade access doesn't. That's the gap Fikra is closing."
James Miano
Founder, Roniki Systems · Nairobi, Kenya
Low-Level Weight Optimization.
To achieve our pricing advantage without burning cash, we optimize the execution model directly. We are actively developing custom pipeline optimizations for Ternary Weight (1.58-bit) LLM architectures.
By quantizing model layers into states of -1, 0, and 1, we eliminate memory-intensive matrix multiplications entirely. Hardware runs fast, power consumption drops, and you gain scalable economics.
// Quantize matrix weights to ternary states (-1, 0, 1) fn quantize_1_58bit(weight: f32, scale: f32) -> i8 { let normalized = weight / scale; if normalized > 0.5 { 1 } else if normalized < -0.5 { -1 } else { 0 } } // Inference matrix addition replacing multiplication for weight in model_layers { match weight { 1 => output += input, -1 => output -= input, 0 => continue, } }
James Miano
- → Self-taught AI/ML engineer focused on inference optimization.
- → Designing hardware-accelerated backend architectures.
- → Advocating for localized infrastructure in the global South.
Get in Touch
Looking for pricing optimizations, architectural insights, or want to discuss enterprise integrations? Reach out directly.