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Energy Metering Intelligence Platform
A consultant-grade energy analysis dashboard built for smart building feasibility studies, investment appraisals and sustainability reporting.
Designed for asset owners, property managers, technical directors, and sustainability leads.
What it does:
Ingests circuit-level metering data (CSV/Excel) and runs a full analysis pipeline — energy performance, load profiling, consumption patterns, baseload analysis, and demand benchmarking against CIBSE TM46 office standards
Detects control deficiencies automatically — out-of-hours usage, high baseload ratios, poor load factors — and generates structured findings with root causes, severity ratings, and savings potential
Financial modelling with configurable tariffs, carbon factors, and circuit coverage scaling — calculates cost, carbon emissions, and intensity metrics per square metre
Scenario analysis for 8 specific smart building measures (HVAC scheduling, lighting controls, BMS optimisation, etc.) with NPV, payback period, and IRR calculations across three implementation packages
AI-powered knowledge base using RAG (Retrieval-Augmented Generation) — upload building documents (surveys, O&M manuals, metering schedules), and the system extracts facts, provides semantic search, and enriches analysis with document-backed evidence and citations
Professional report generation — exports to Word (DOCX) and PDF with narrative-driven insights, executive summaries, and document reference citations suitable for board-level feasibility reports
MCP server integration — exposes building analysis data to Claude Desktop via 7 tools, enabling natural language querying of energy data, control findings and feasibility summaries
Multi-building portfolio support with persistent storage, vendor solution mapping and predictive analytics using weather data from Open-Meteo
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
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A goal-tracking sub-system that grounds an AI assistant in the user's full life-state — target amount, hard deadline, days remaining, current balance, pace status (ahead / on-pace / behind), and reflection streak.
Core features:
Multi-entry timestamped reflection log — plain Enter submits, Shift+Enter newline, optimistic UI, all entries inside one unified container with centered timestamp dividers
Ephemeral Summarize chat modal — loads today's braindumps as live AI context, brother-tone system prompt, conversation NOT persisted (privacy by design)
Nightly auto-summary cron at 23:55 — pulls reflections, runs through Claude, creates a standalone daily summary that downstream AI engines pick up automatically
Pace analysis — surfaces required-vs-actual daily rate, projected gap at deadline, status flag
Each AI engine pulling this data adapts its suggestions based on whether the user is ahead or behind on their goal — recursive context that compounds over time.
Tech: Claude API, SQLite, Node.js cron, custom retrieval logic.
A goal-tracking sub-system that grounds an AI assistant in the user's full life-state — target amount, hard deadline, days remaining, current balance, pace status (ahead / on-pace / behind), and reflection streak.
Core features:
Multi-entry timestamped reflection log — plain Enter submits, Shift+Enter newline, optimistic UI, all entries inside one unified container with centered timestamp dividers
Ephemeral Summarize chat modal — loads today's braindumps as live AI context, brother-tone system prompt, conversation NOT persisted (privacy by design)
Nightly auto-summary cron at 23:55 — pulls reflections, runs through Claude, creates a standalone daily summary that downstream AI engines pick up automatically
Pace analysis — surfaces required-vs-actual daily rate, projected gap at deadline, status flag
Each AI engine pulling this data adapts its suggestions based on whether the user is ahead or behind on their goal — recursive context that compounds over time.
Tech: Claude API, SQLite, Node.js cron, custom retrieval logic.
Designed, built and deployed a Prospect Finder tool.
AI-Powered Lead Intelligence & Outreach Platform.
Built a fully custom, AI-powered prospecting and outreach platform from the ground up to power an entire sales operation solo, without an engineering team.
The platform functions as a complete sales intelligence command center, pulling prospect data across multiple sources simultaneously; Google Maps, LinkedIn, business websites, Yelp, Facebook, license databases, and directories and scoring each lead with a proprietary AI Fit Score to prioritize outreach by conversion likelihood.
From there, the system manages the full 8-touch outreach campaign lifecycle per prospect, tracking each contact’s position across the sequence in real time. When prospects reply, the platform surfaces AI-generated response suggestions tailored to the conversation context, allowing instant, intelligent follow-up with a single “Approve & Send.”
What I built:
[] Search Command Center with multi-source data scraping (Google Maps, LinkedIn, Yelp, Facebook, Licenses, Directories)
[] AI Fit Scoring engine that ranks prospects by conversion likelihood
[] 8-touch campaign status tracker per contact
[] AI-suggested reply system with Ignore / Edit / Approve & Send workflow
[] Lead management dashboard with overview, replies, leads, campaigns, network, and archives modules
[] Export functionality for pipeline data
Platform tools of dev: Agentic AI development workflows, Claude API, n8n automation, no-code platforms.
End product output: A single operator running a sales intelligence and outreach system that would typically require a dedicated SDR team and a $30k+/year software stack. Built and deployed solo in weeks.
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