Artificial intelligence that cites the project and regulatory documents it uses

Ask AI, Review with AI and Draft with AI work from the project’s documents and registers and the regulations for its jurisdiction. Specialists review what they produce, and each export records where artificial intelligence was used.

A question about what the Environmental Statement commits to for ground-nesting birds during construction, answered with numbered sources from the chapters, the Outline Construction Environmental Management Plan and the commitments register. Hartsmoor Solar Farm is a fictional demo project.

Ask AI

Questions about the project, answered with numbered sources.

Answers come with numbered sources a reviewer can open, and name the model that wrote them. Where nothing in the project or the regulations supports an answer, Ask AI says so.

Ask AI sources list. Each numbered source names the document and the section or paragraph, for example Chapter 8 Biodiversity section 8.6 and the Outline Construction Environmental Management Plan section 5.4, or a commitments register entry.
An Ask AI answer with its numbered sources, each naming the document and section or the register entry.
Ask AI answering “What did the landowner agree at the July site meeting?” by saying the approved material does not record any landowner agreement at a July site meeting.
Asked about a July site meeting, Ask AI says the project’s documents hold no record of one.
Two questions to Ask AI. One is answered with numbered sources, and the project holds nothing on the other.

The project knowledge graph

The project is kept as linked facts, so Ask AI answers a question that runs across chapters and registers from the record, with each entry cited.

Most tools answer by searching the documents for the passages closest to the question and handing them to a model. That works for one fact in one place. The questions an assessment turns on are usually chains: the impact is in one chapter, the mitigation in another, the commitment that secures it is in a register, and the duty it discharges is in the regulations. No single passage holds the answer, so a search-and-summarise tool guesses at the join or misses it.

EcoSphere Intelligence keeps the project as a knowledge graph: the site and its designations, the receptors, the impacts on them, the mitigation, the commitments and conditions that secure it, the chapters that report them, and the statutory duties each topic carries. Each link points back to the passage it came from, and a fact read from a document stays a proposal until a specialist approves it.

Ask AI reads that record directly. A question about which, how many or what status is answered from the registers. A chain question, for example which commitments secure the mitigation for each scoped-in water impact and which chapters report them, is answered by following the links, with each register entry cited the way a passage is. Where the record and the documents hold nothing, it says so.

Diagram of the project knowledge graph showing the project, its site, constraints, scope proposals and decisions, commitments, report sections, cumulative schemes and documents, with the reference data each links to and the number of links on each line.
The project knowledge graph for a solar farm: the site, its constraints and their designations, the scope proposals and decisions, the report sections, the commitments and the documents behind them.

Review with AI

A chapter’s claims checked against the project’s documents and the requirements for that section.

Before a chapter reaches the reviewer, each claim has been checked against the project’s documents and each section against what the regulations require of it, with the passage behind every finding. The reviewer starts from the findings.

Review with AI results for a chapter, listing each claim with its verdict and the quoted source passage and page.
Review with AI findings. Each claim is marked Supported, Unsupported or Uncertain, with the source passage and page it was checked against.
A chapter checked with Review with AI, corrected and sent to a named reviewer for approval.

Draft with AI

First drafts of sections from the project’s sources, with the sources cited.

First drafts come from the project’s own sources with the citations in the text, and Draft with AI declines where it has no evidence. A specialist reviews every draft before it goes in.

Environmental Statement section drafted with Draft with AI, with its source references.
A section drafted with Draft with AI, with the sources it cites.

The regulations behind the answers

Each regulatory pack holds the regulations and guidance for one jurisdiction.

Ask AI answers from the regulations and guidance for the project’s jurisdiction, alongside the project’s own documents and registers.

Records of artificial intelligence use

Your quality and technology leads can see where artificial intelligence was used, by whom, with which model, and what it cost.

Each export carries an artificial intelligence use statement, each run is in the workspace audit log, and owners and admins see spend against a monthly cap. We instruct our model providers, by contract, not to use your prompts, inputs or outputs to train their models (Privacy Policy, section 4).

Month-to-date artificial intelligence spending, broken down by task and project.
Artificial intelligence spending for the month.

See EcoSphere in a demo

Follow an assessment through to an approved Environmental Statement.

We show source checks, chapter review and the approved export on a fictional project, then talk about your consenting regime and how your team works.