Utility Carbon Reporter

For

Sustainability leads at facilities management companies, commercial property managers and mid-sized logistics firms

Solves

Manual sustainability reporting from utility bills is repetitive, error prone and steals time from client relationships.

Delivers

Client-ready carbon reports with methodology notes, charts, source citations and year-on-year comparisons

Built in

about 2 weeks of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $17,000 for the full product

Run it

Inside your business, or as part of your offer to clients

For sustainability leads at facilities management companies, commercial property managers and mid-sized logistics firms, turn utility invoices and meter data feeds into client-ready carbon reports with methodology notes and year-on-year comparisons.

1. Extract line items from utility invoices and meter feeds.
2. Classify energy, water and waste categories.
3. Map each line to an emissions factor from a maintained library.
4. Calculate scope 1 and 2 emissions with standard factors.
5. Build a draft report in the client's template with charts and citations.
6. Route the draft to a human reviewer for approval or correction.

What goes in, what comes out

The workflow

1. In
   Start with

   Utility invoices, meter data feeds, client templates and emissions factor preferences

2. 1

   Connect utility accounts or forward invoices

3. 2

   Ingest and extract line items

4. 3

   Classify categories

5. 4

   Map emissions factors

6. 5

   Calculate scope 1 and 2 totals

7. 6

   Generate draft report with charts and methodology

8. 7

   Review and approve

9. 8

   Then export client-ready PDF

10. Out
    Finish with

    Client-ready carbon reports with methodology notes, charts, source citations and year-on-year comparisons

AI does the heavy lifting, people stay in charge

Use language models and OCR to extract and classify line items from varied invoice formats, and rule-based mapping to emissions factors. Keep extracted values in structured fields with confidence scores. A human reviewer checks numbers and adds notes before any report is sent.

What your team sees

Key screens: Ingest queue, extraction review, calculation workspace, report builder. Use a dashboard for incoming bills and data feeds, a line-item extraction view with confidence flags, a calculation panel with emissions factors, and a report preview with charts and methodology notes. Display statuses: ingested, extracted, calculated, awaiting review, approved. In this product, the first view is ingest queue, followed by extraction review and report builder.

Accounts and administration

Accounts for reviewers and approvers, report versioning, approval states, audit trail of extraction and calculation steps, and permissions per client account.

Integrations and data access

Utility provider portals and APIs, email inbox for forwarded invoices, PDF parsers, and export to PDF or CSV for client reports.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   2 days

   One buyer segment, one recurring use case; first modules: invoice ingestion and emissions calculation with a single global factor. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   6 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will sustainability leads at facilities management companies, commercial property managers and mid-sized logistics firms use it to solve "manual sustainability reporting from utility bills is repetitive, error prone and steals time from client relationships"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. A paid pilot with one facilities management client for three months, measuring report cycle time and error rate against their current manual baseline.
4. Measure, then decide. Track report cycle time reduced from five days to under one day. Error rate in emissions calculations reduced to zero in approved reports. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One buyer: facilities management companies. One use case: electricity reporting. First two modules: invoice ingestion and emissions calculation with a single global factor. Manual review of every report before export.

After the MVP. After the paid pilot, automate water and waste categories, add provider-specific parsing rules, integrate with meter APIs, and offer automatic year-on-year comparisons and client-branded PDF generation.

What the build depends on. Technical build needs access to OCR and language model APIs, a structured emissions factor database, and a secure document storage layer.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test pricing at USD 1,500 per client per month, with a setup fee of USD 5,000, as a hypothesis.

Message to test

Turn your utility bills into client-ready carbon reports without touching a spreadsheet.

Where to find buyers

Industry associations for facilities management, sustainability conferences, LinkedIn groups for property managers, and direct outreach to firms with public sustainability commitments.

Lead magnet

A free sample report generated from one month of a prospect's electricity bills, showing the format and methodology.

The first 30 days

1. Week 1: Set up ingestion for one utility type and build extraction pipeline.
2. Week 2: Implement emissions calculation with a single global factor.
3. Week 3: Build the draft report template with charts and methodology notes.
4. Week 4: Test with a friendly client, refine review workflow and prepare pilot materials.

Paid pilot

A paid pilot with one facilities management client for three months, measuring report cycle time and error rate against their current manual baseline. Decision to continue if cycle time drops by at least 50% and the client approves reports without major corrections.

Success metrics

Report cycle time reduced from five days to under one day. Error rate in emissions calculations reduced to zero in approved reports.

Retention and expansion

It keeps earning through monthly subscription, with the system learning provider-specific formats and building a library of client templates that make each report faster to produce.

Why clients would pick it

The emissions factor library and provider-specific parsing rules grow with every client, making the system faster and more accurate over time while competitors start from scratch.

Alternatives and positioning

Spreadsheets and manual data entry, generic accounting software, or outsourced consultants. This differs by automating the extraction and calculation while keeping a human in the review loop.

Main delivery costs

Main delivery costs are cloud hosting, OCR and language model API usage, and initial integration work per utility provider.

Limit access to approved reviewers only, require human approval before any report is exported, log all corrections and overrides, and never auto-send reports without an explicit approval step. It must not calculate emissions for categories without a verified factor.