Pursue bold AI foundations.
Build toward AGI with new learning ideas.
NektronAI started with one core thesis: current AI approaches may not be enough. Our research explores, through GrowNet, a biologically inspired direction where learning is local, event-driven, and growth-aware, while staying pragmatic instead of copying biology end-to-end. Our products exist to generate revenue and real-world pressure that sustains this long-horizon research.
Two pillars
NektronAI is organized as a research-product loop: research develops bold new learning primitives, and products stress-test them against changing distributions, latency constraints, and real user behavior.
AI Research
Our research explores local, event-driven learning and controlled growth through GrowNet as a biologically inspired but engineering-grounded alternative to heavyweight global training pipelines.
AI Applications
DeepTrading.ai, InterviewHelperAI, and TagMySpend.com are practical proving grounds and revenue engines that keep long-horizon research active.
Research: GrowNet
GrowNet is the centerpiece R&D effort: a neuron-centric architecture where each neuron maintains inspectable memory slots, updates locally per event, and expands capacity from slots to larger structures only when novelty requires it. The direction is biologically inspired, but intentionally not biologically dogmatic.
What it is
A research architecture where neurons keep small slot tables and learn event-by-event with local updates, not one global backprop-style loop.
- Local learning per neuron
- Inspectable slot memory that records recurring patterns
- Tick-driven execution for continuous adaptation
- Growth mechanics: slots → neurons → layers → regions
- Cross-language parity (Python, Java, C++, Mojo)
Status
GrowNet is under active development and is not yet integrated into NektronAI’s products. It is being built as a research claim with benchmark targets, with the long-term aim of becoming a shared future foundation.
The architecture, claims, and benchmark goals are evolving. We prefer measured evidence over broad promises.
“When something truly new shows up, make room. If it isn’t truly new, improve what you already have.”
Products
Each product is a proving ground where ideas meet changing user needs, latency constraints, and measurable outcomes.
DeepTrading.ai
Stock research platform focused on forecasts, backtesting, and transparent performance tracking.
InterviewHelperAI
AI-powered interview practice and preparation workflows designed for clarity and fast iteration.
TagMySpend.com
Spending organization with automation-first categorization and audit-friendly outputs.
Current products do not yet use GrowNet. GrowNet is being developed as a future research foundation.
Contact
For collaborations, product partnerships, or research discussions:
Company
Nektron, Inc.