AIData Systems & AI LabProduct Analytics · Data Systems · AI Workflows · Decision InfrastructureContact
Open OS launcher
NewOperating layer for product analytics, data systems, AI workflows, and business decisions.View projects

Product, Data & AI Systems for Modern Tech Teams

I build decision infrastructure: SQL warehouses, product analytics, business analysis, dashboards, AI-assisted workflows, and agent-ready systems that turn operating data into product and business decisions.

workspace.command

$ open beheiry.dev/projects --focus budgetdb ghost-ai dashboards

Case-study systems for analytics, AI workflows, and decision infrastructure.

/portfolio/projects

case-studies.index

decision-infrastructure.log

# Build analytics warehouse

$ psql budgetdb --run models/finance_workforce.sql

CREATE VIEW analytics.v_exec_ops_annual ... DONE

QA checks: source totals reconciled · variance within threshold

# Generate product decision brief

$ ai summarize --inputs sql,dashboard,roadmap

Signals: churn risk, cost concentration, adoption friction

Output: executive notes, KPI risks, recommended next actions

31+

SQL views and checks

BudgetDB-style warehouse logic, executive views, and QA validation.

98%

QA pass target

Reconciliation-first thinking for trusted business reporting.

30%

manual reporting reduction

Automation mindset across reporting, dashboards, and recurring analysis.

10K+

engagement lift analyzed

Product analytics, retention, churn, funnels, and stakeholder reporting.

Case studies

Systems work, framed as product evidence

The work is organized around business questions, technical implementation, and decision impact.

ghost-ai.case-study

AI-native systems platform

Ghost AI — Collaborative AI Architecture Workspace

Under Active Development

Production-grade AI-powered architecture and workflow builder with realtime collaboration, AI-assisted systems design, and interactive canvas orchestration.

Business question

How can product, analytics, and engineering teams design AI systems collaboratively while keeping architecture, workflow orchestration, and implementation context in one place?

Positions Ghost AI as an AI-native product, analytics, and systems orchestration platform for collaborative system design, product/spec generation, background AI workflows, and production debugging.

Next.jsTypeScriptLiveblocksTrigger.devPrismaPostgreSQLOpenRouterReact Flow
View case study
Ghost AI — Collaborative AI Architecture Workspace preview

budgetdb.case-study

Flagship system

BudgetDB Operations Analytics Warehouse

Flagship

A Postgres-backed operations analytics system that turns budget, vendor, software spend, and headcount data into trusted executive views.

Business question

Where is operational spend concentrated, and how should leadership prioritize the next planning cycle?

Creates a reusable decision layer: cleaned tables, composable views, spend allocation, QA checks, and executive-ready outputs.

PostgreSQLBudget AnalysisOperations AnalyticsExecutive Reporting
View case study
BudgetDB Operations Analytics Warehouse preview

executive-dashboards.case-study

Dashboards

Executive KPI Dashboards

Live

Dashboard views for contact center performance, revenue mix, product trends, and executive operating reviews.

Business question

What does leadership need to see quickly to understand performance, variance, and where to investigate?

Makes KPI patterns easier to scan and turns analysis into a review-ready operating surface.

TableauKPIsRevenueSupport Operations
View case study
Executive KPI Dashboards preview

Technical systems panel

Technical Stack / Tools I Work With

A practical operating system of product, data, AI, SaaS, and analytics tools used across dashboards, automation, product delivery, and business decisions.

technical_stack.logo_wall

Data Sources & Storage

/tools/data-sources

Postgres / PostgreSQLprimary database
SQL Databases
Supabase
Snowflake
BigQuery
Redshift
MySQL
MongoDB
Google Sheets
CSV / Excel Data
CRM Data
Product Usage Data

Manage & Query

/tools/manage-query

SQLanalytics query
Pythonprimary coding
Data Modeling
Data Cleaning
BI
Dashboards
Reporting Automation
KPI Design
Funnel Analysis
Cohort Analysis
Retention Analysis
Churn Analysis
A/B Testing
Statistical Analysis

Apps, SaaS & Integrations

/tools/apps-integrations

Clerk
Supabase
Vercel
Next.js
React
Tailwind CSS
GitHub
Git
APIs
ENV / Config
Authentication
Stripe
Zapier / n8n-style automation
Webhooks
CRM
Jira
Confluence
Figma
Mural
Smartsheet
Azure DevOps

AI / ML / Agent Systems

/tools/ai-ml-agents

OpenAI
ChatGPT
Claude
LangChain
LangSmith
Pinecone
Vector Databases
RAG
Embeddings
Prompt Engineering
AI Agents
Agent Mode
MCPs / Model Context Protocol
Markdown / .md Docs
Plugins
Skills
Automations
Agent Tools
Tool Calling
Context Engineering
Workflow Orchestration
Prompt / Instruction Files
AI Operating Procedures
AI-assisted Documentation
Reusable Agent Workflows
Human-in-the-loop Review
Task Automation
LLM Workflows
Model Evaluation
Workflow Automation
Supervised Learning
Unsupervised Learning
Regression
Classification
Clustering
Forecasting
Recommendation Systems
Anomaly Detection

Product / Business / FinTech

/tools/product-business

Product Management
Product Analytics
Roadmaps
PRDs
User Stories
Backlog Prioritization
Stakeholder Management
Business Analysis
Operations Analysis
Market Analysis
SaaS Systems
FinTech Systems
Retirement / Financial Services
Billing Systems
Compliance Workflows
QA / UAT
Process Improvement

Operating system

Product, analytics, business, and AI modules

A recruiter or founder should be able to scan the page and understand the work surface quickly.

capability_modules
module

Product Strategy

Roadmaps, PRDs, stakeholder alignment, business requirements, and tradeoff framing.

module

Analytics

Funnels, retention, cohorts, churn, KPI design, dashboards, and experiment interpretation.

module

Business Analysis

Financial operations, process maps, reconciliation, reporting logic, and decision support.

module

AI Workflows

Prompt systems, LLM workflows, RAG concepts, agent architecture, and AI-assisted development.

module

Technical Teams

AI products, SaaS workflows, financial systems, customer operations, and data-driven product decisions.

Analytics console

Dashboards, SQL, and AI summaries in one decision layer

A compact product console showing how the portfolio connects data models, quality checks, product analytics, and AI-generated operating notes.

product_analytics_workspace
SELECT team, cost_category,
       SUM(amount) AS spend,
       RANK() OVER (
         PARTITION BY team
         ORDER BY SUM(amount) DESC
       ) AS priority
FROM budgetdb.fact_spend
WHERE period = 'current_qtr'
GROUP BY team, cost_category;

warehouse

31 views

Postgres models refreshed

quality

98% target

variance checks completed

product

+10K signal

activation funnel reviewed

workflow

exec-ready

AI summary generated

Code proof

BudgetDB is shown through SQL and QA logic

The flagship case study demonstrates data modeling, business analysis, QA checks, and executive reporting.

code-proof.workspace

Code proof

1CREATE VIEW analytics.v_software_cost_per_employee_company_2025 AS2WITH employee_count AS (3  SELECT COUNT(*)::int AS total_employees_20254  FROM analytics.dim_employee5  WHERE (start_date IS NULL OR start_date <= '2025-12-31'::date)6    AND (end_date IS NULL OR end_date >= '2025-01-01'::date)7),8company_spend AS (9  SELECT SUM(COALESCE(total_spend_2025, 0))::numeric AS total_software_spend_202510  FROM analytics.vendors_2025_clean11)12SELECT13  c.total_software_spend_2025,14  e.total_employees_2025,15  ROUND(c.total_software_spend_2025 / NULLIF(e.total_employees_2025, 0), 2)16    AS software_cost_per_employee_202517FROM company_spend c18CROSS JOIN employee_count e;
why_me.profile

I turn business questions into decision infrastructure: SQL/Postgres workflows, executive dashboards, KPI frameworks, QA checks, budget models, churn analysis, product usage analysis, and AI-powered workflows that help teams move from raw data to confident decisions.

My background sits across product management, business analysis, FinTech/SaaS operations, product analytics, and applied AI. I connect strategy with execution by translating stakeholder needs into requirements, building dashboards and reporting systems, validating metrics, and designing workflows that make decisions faster and cleaner.

I recently built and deployed this AI/analytics portfolio platform using Next.js, React, TypeScript, GitHub, and Vercel, with CI/CD, custom domain routing, and a scalable structure for showcasing data systems, AI workflows, and product case studies.

My work includes BudgetDB, an operations analytics warehouse; SQL reconciliation systems; executive dashboards; Python-based churn modeling; and Chorus, an AI-agent learning product focused on workflows, agent skills, memory, and decision systems.

I focus on building systems where SQL, dashboards, APIs, product thinking, metrics, and AI workflows come together into end-to-end decision infrastructure.

Portfolio: beheiry.dev

Warning: excessive exposure may cause roadmap clarity, cleaner metrics, and fewer spreadsheet fires.