AIGNITE
We build AI that works —
from drug discovery to field robots.
AIGNITE exists because the value of AI is realized only when it ships — as a product someone uses, a system someone relies on, a tool that quietly works. Everything on this page is evidence, not promise: systems we have built and domains we have shipped into.
Start a conversationMulti-provider LLM integration behind an abstraction layer, RAG, schema-constrained output, real-time audio, prompt-cache cost engineering, and prompt-injection defense-in-depth.
Multi-task deep networks, gradient boosting, time-series forecasting, interpretability with SHAP, and small-data rigor with honest uncertainty.
YOLOv8 detection and segmentation, edge + cloud inference splits, classical CV, and real-time browser detection at interactive frame rates.
Molecular docking, ADMET screening, fragment-based de novo design, adsorption-cycle simulation, techno-economic optimization, and physics + ML hybrids.
Desktop apps with embedded scientific Python, React web, React Native mobile, offline-first PWAs, and real-time WebSocket systems — shipped end to end.
Microcontroller firmware with fail-safes, RTK GNSS positioning, checksummed UART protocols, sensor integration, and on-device inference.
Serverless containers, edge functions with geo-gating and rate limiting, size-optimized Docker images, and scheduled serverless crawlers.
We start with the problem, not the model — and tell you honestly whether AI is the right tool for it.
A working slice early: real data, real constraints, honest uncertainty — before anything is scaled.
Desktop, web, mobile, edge, or firmware — the whole system, engineered and delivered end to end.
Cost engineering, rate limiting, monitoring, and defense-in-depth — so it keeps working after launch.
portfolio shown at sector level — client details stay confidential
biomedical · pharma r&d
Multi-task deep-learning resistance prediction paired with molecular docking, ADMET screening, and fragment-based de novo design — packaged as a cross-platform desktop app with an embedded scientific Python runtime.
climate tech · ccu
A hybrid physics + machine-learning platform: ML over experimental catalysis data, an adsorption-cycle simulator, and a techno-economic optimizer — a bilingual cloud web app with emissions forecasting.
precision agriculture
A sensor-equipped field robot with RTK positioning streaming crop imagery to cloud-hosted YOLOv8 inference — real-time dashboard, advisory engine, and mobile push alerts, from firmware to cloud.
education · music
Schema-constrained LLM lesson and quiz generation combined with real-time browser audio: live pitch detection for vocal coaching, streaming audio to multimodal models, and a multi-instrument simulator.
civic services · client work
An offline-first PWA guiding users through administrative forms: a zero-cost deterministic instruction layer plus a geo-gated, rate-limited LLM chat backend on edge serverless — lexical RAG that cuts prompt tokens 4–10×.
ignite( your idea )
Tell us what you're trying to build — we'll tell you honestly whether AI is the right tool.