AI infrastructure, automation and intelligent developer tools.
Alsaidy AI Labs is an early-stage, self-funded AI startup building open-source and product-focused tools for AI model orchestration, developer automation, benchmarking, and specialized AI applications.
Core Focus
What We Build
We're building modular software for AI model management, developer automation, and computational research.
AI Model Orchestration
Building a unified API layer to connect and manage multiple AI providers — AWS Bedrock, Anthropic, OpenAI, and self-hosted models — behind a single gateway.
Multi-Model Routing
Developing intelligent request routing that selects models based on task complexity and cost constraints, with automatic fallback between providers.
Agent & CLI Delegation
Creating task decomposition tools that allow agents to spawn, coordinate, and delegate subtasks across terminal and cloud environments.
Cost & Usage Analytics
Designing dashboards and logging infrastructure for per-request token accounting, latency tracking, and monthly spend projections.
AI Benchmarking
Building evaluation harnesses to measure latency, throughput, accuracy, and cost across different foundation models and providers.
Research Tools for Life Sciences
Applying AI and computational methods to microbiology — including fungal morphology analysis, genomic sequence processing, and lab data automation.
AI Model Orchestrator
A platform for managing multiple AI providers and models through a single API — with routing, fallback, cost tracking, and benchmarking capabilities.
What We're Building
A single API gateway that abstracts across AWS Bedrock, Anthropic, OpenAI, and local models.
Automatic provider fallback — if one provider hits rate limits, traffic reroutes to the next available.
Intelligent routing that matches task complexity to the right model tier to reduce costs.
Per-request token usage logging and cost tracking across all connected providers.
Stack
Status: In Development — actively being built and iterated on.
Open-Source & Active Work
Projects
Tools and frameworks currently being developed. Source code repositories are published on GitHub as each project reaches initial release.
AI Model Orchestrator
A platform for managing multiple AI providers and models through a single API — with routing, fallback, cost tracking, and benchmarking capabilities.
Multi-Model Router
A routing proxy for LLM requests that selects the best provider based on cost and task complexity, with automatic fallback handling.
Agent Delegation CLI
A lightweight command-line toolkit for coordinating background agent tasks and managing subagent workflows.
AI Benchmarking Suite
An evaluation framework for measuring latency, throughput, cost, and output quality across different AI models and providers.
Fungi.ai
A computer vision and genomic analysis pipeline focused on fungal morphology identification and microbial classification.
Developer Profile & Repositories
Active experiments, scripts, and work-in-progress on GitHub.
AI × Life Sciences
Research & Scientific Work
Bridging microbiology and software engineering — applying computational methods to biological problems and life sciences data.
AI × Environmental Microbiology
Applying computational methods and machine learning to microbial bioremediation, cyanobacteria growth dynamics, and pollutant degradation mechanisms.
AI Model Infrastructure
Designing multi-provider orchestration architectures, cost-optimization strategies, and autonomous agent evaluation frameworks.
Computational Bio-Pipelines
Building open-source tools for genomic sequence annotation, laboratory data processing, and microbiological image analysis.
Combining microbiology domain knowledge with computational and machine-learning pipelines to advance bioremediation research and microbial analysis.
Built with AWS
Our infrastructure architecture is being designed around Amazon Web Services for model access, distributed compute, telemetry, and research artifact storage.
Python SDK, Next.js UI, & CLI Agent delegation tools.
SSL termination, request throttling, and token authentication.
FastAPI router core, dynamic complexity classification, and failover logic.
Claude 3.5 Sonnet, Claude 3.5 Haiku, and specialized bio-reasoning models.
Stores benchmark evaluation runs, prompt regression test cases, fungal microscopy datasets, and genomic sequence cache.
Continuous latency logging, token spend monitoring, provider error alarms, and automated failover telemetry.
AWS Bedrock
Multi-model foundation model access and provider abstraction.
AWS Lambda / ECS
Planned compute layer for routing and background workloads.
Amazon S3
Storage for evaluation artifacts and research datasets.
Amazon CloudWatch
Observability, latency monitoring, and usage telemetry.
Infrastructure Roadmap & Resource Allocation
AWS Activate credits will support the development and testing of the platform's model orchestration, evaluation, and cloud infrastructure.
Stack
Technology
The providers, languages, and infrastructure we work with.
AI Providers & Planned Integrations
Languages & Frameworks
Infrastructure
Leadership
Founder
Ahmed Makram Siddek Alsaidy
Founder & Software Engineer
Microbiology researcher working at the intersection of AI, software engineering, and life sciences. Building intelligent systems and computational tools to accelerate scientific discovery and developer workflows.