Retail & E-commerce
Customer intelligence, demand forecasting, product discovery, pricing, loyalty, churn, and AI voice support.
AI/ML Consultancy
Research, modeling, and deployable AI systems.
What Spyder Science Does
We focus on AI systems that need more than a demo: grounded evidence, clear assumptions, domain knowledge, model validation, and workflows that teams can actually use.
Customer intelligence, demand forecasting, product discovery, pricing, loyalty, churn, and AI voice support.
Computational modeling, health data analytics, evidence-grounded workflows, and decision-support prototypes.
Applied mathematics, statistics, optimization, simulation, RAG systems, and governed AI workflow design.
Capabilities
Use-case discovery, feasibility assessment, MVP planning, model selection, and evaluation design.
Retrieval systems, SQL-connected assistants, document intelligence, agentic workflows, and guardrails.
Forecasting, simulation, optimization, uncertainty, experimental design, and statistical modeling.
Dashboards, APIs, Docker-based delivery, CI/CD, monitoring, and reproducible production pipelines.
Products
Weli AI and RecepAI show how Spyder Science turns research workflows and retail automation challenges into reusable product platforms.
Governed Decision Workflows
Workflow-Engineered Logical Inference for evidence-grounded reasoning, human-in-the-loop model approval, simulation, validation, and reporting.
Retail Voice Automation
An AI Voice Agent foundation for product discovery, order support, customer service, and commerce engagement in retail and e-commerce.
How We Work
Every engagement is structured to reduce ambiguity and move from problem framing to usable evidence-backed outputs.
Clarify the business or research question, data landscape, constraints, and decision requirements.
Select modeling approaches, workflow architecture, validation criteria, and measurable outcomes.
Build working notebooks, APIs, dashboards, RAG workflows, simulations, or voice-agent prototypes.
Test assumptions, review outputs, document limitations, and prepare a responsible deployment path.
Course Spotlight
Learn practical AI workflows with Python notebooks, embeddings, ChromaDB, RAG, ReAct, evaluation, and capstone-based learning.
Start a Conversation
Let’s define the decision, the data, the model, and the path to a useful working solution.