From scans to answers, not archives.
Pulse turns static documents into infrastructure — structured, decision-ready data you can talk to, build on and compound. Mining-trained, source-cited, validated past 99% on the hardest data.
Your data is digital. But it isn't intelligence.
Decades of geological reports, drill logs and filings sit in scanned PDFs, images and handwritten archives — and a live flood of new disclosure lands every day. All of it digital. None of it usable by AI.
~5%
What basic OCR actually recovers from dense technical scans.
15+ hrs
Per analyst, per week, lost to finding data instead of using it.
90%
"Accurate" is unusable — at that level every cell has to be re-checked by hand.
Two waves of digitisation
The first made documents digital. The second makes the data usable. Pulse delivers the second.
Wave one · Storage
×
Let's get rid of paper
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Scanned JPEGs and fuzzy PDFs
×
Text trapped inside images
×
Searchable by filename only
×
Digital filing cabinets, not intelligence
Wave two · Structure — the Pulse layer
→
Machine-learnable, structured data
→
AI can read, link and reason over it
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Every figure normalised and typed
→
Query in plain language
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Every answer cited back to source
Why scanned PDFs don't work for AI
To a machine, a scan is a photo. The information has to be rebuilt before AI can use it.
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Images of text
Blurry, skewed, multi-column scans where every word is just pixels — invisible to a model.
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Handwritten & stamped
Soviet-era logs, marginalia and degraded scans that off-the-shelf OCR can't touch.
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Maps & drill logs
Coordinates, sections and schematics carry the geology — and none of it is text.
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Crushed tables
Assay and resource tables collapse into noise; rows, columns and units are lost.
One automated pipeline, end to end
Documents land and the pipeline runs without manual intervention — ingest to answer.
Ingest
Secure, encrypted pipeline with a dedicated environment per client — your data, your boundary.
OCR & translate
97%+ word, 99%+ character accuracy. Bilingual output, original layout and tables preserved.
Structure & normalise
Typed schemas, unit standardisation, 100+ commodities, coordinate systems captured natively.
Validate
Raw extraction sits in a holding layer; human sign-off promotes it to a clean master dataset.
Talk to it
Query in plain language on the platform — or connect your own AI agent via the Pulse MCP.
Proven at scale, validated past 99% on the hardest data
Over 24 million pages digitised to date — including individual archive projects exceeding 4 million pages. Ground-truth validated on dense, Cyrillic, Soviet-era assay data, across all four report families.
24M+
Pages digitised across engagements to date
99.21%
Element accuracy, ground-truth validated
4M+
Pages in a single archive project
99.65% / 99.06%
Recall / precision on assay extraction
Source: Pulse Intelligence corpus and benchmark, anonymised · 2026
Real-time insights from millions of documents
Tailored to mining. Delivered in seconds. Watch how a corpus of scans becomes a structured, queryable intelligence layer.
See the geology, not just the text
The same structured corpus renders spatially — including 3D drill-hole visualisation, shipping in production.
3D collars & intercepts
Surface-topography adjusted, so underground intercepts map correctly against terrain.
Spot the "dud" holes
Un-assayed drill holes that selective reporting tries to hide become obvious at a glance.
History on a time-slider
Watch drill holes appear over time; diff what changed between announcements.
Lives inside ArcGIS Pro
A Pulse-served spatial layer — your team works where it already works.
The same corpus, rendered as intelligence
Once structured, the data surfaces across the Pulse front end — drill results, reserves and resources, and spatial views, every figure one click from its source document.
Drill results, coloured by grade. 637 holes across every disclosure, graded and source-linked.
Collars on the map. Holes plotted on satellite imagery, georeferenced from the source archive.
Reserves & resources, over time. Every estimate normalised, tracked across announcements, traceable to source.
One project, every view. Exploration, tenements and production from a single structured corpus.
Illustrative views, publicly listed company · Pulse Intelligence platform
More than OCR. More than search. More than a chatbot.
OCR gives you words. Search gives you matches. A generic model guesses. Pulse rebuilds the corpus into a retrievable knowledge base — and gives you cited answers.
| Capability | Basic search | Generic chatbot | The Pulse layer |
|---|---|---|---|
| Understands your question | No | Yes | Yes |
| Answers from your documents | No | No | Yes |
| Knows mining terminology & units | No | No | Yes |
| Cites the source page | No | No | Yes |
| Deep filters: grade, commodity, geography | No | No | Yes |
| Won't invent a number | Yes | No | Yes |
| Private, compliant, auditable | — | No | Yes |
Where structured data changes the work
Legacy archive digitisation
Turn decades of static reports into a searchable, structured dataset with tagging, metadata and clustering.
Technical benchmarking
Compare grades, drill data and production across reports and companies — no spreadsheet cleanup.
Due diligence & deal prep
Find and filter project-relevant files by location, grade or type to accelerate diligence.
Model inputs & dashboards
Feed source-tagged, ready-to-use data into models and dashboards without reformatting.
Digitisation is the first step. Not the last.
Turning your archive into structured data is step one — and for many teams, it's enough on its own. But the same engine keeps ingesting, so your archive becomes the foundation you run your entire geological business on.
Your own archive
Legacy scans, drill logs, maps and field notes — digitised, translated and structured.
Public & regional datasets
Government geochemical surveys, open-file drill-hole databases and survey reports — onboarded jurisdiction by jurisdiction.
Tenement & disclosure
Tenement and relinquished-ground reports, plus live filings and drill results from public markets.
↓
↓
Build once. Compound forever.
Every dataset, module and deal builds on the same structured foundation — so the asset appreciates instead of ageing.
01 · Lay the foundation
Your archive, structured — Validated, normalised and source-linked. A single, trusted base layer instead of scattered files.
02 · Compose on top
Add sources & modules — Public and regional data, comparables, occurrence intelligence, risk surveillance and spatial layers — all on the same base.
03 · Compound with every deal
Never start from scratch — Each diligence, acquisition or new dataset builds on what's already there — value accrues with every addition.
From stored to understood
A private, mining-trained intelligence layer your team can actually run on — at a fraction of the cost and time of doing it by hand.
90%+
Reduction in research time — months of manual work become instant answers.
1 reviewer
To check output. No new hires — QA shifts to the people who know the rocks.
Up to 70%
Of cost saved, and 12+ months faster, versus manual digitisation.
Source: Pulse Intelligence client engagements, anonymised · 2026
Questions, answered
What does Pulse's data cleansing and digitisation actually do?
Pulse converts static documents — scanned PDFs, images, maps, drill logs and handwritten archives, plus live disclosure — into structured, source-linked data you can query in plain language. It goes beyond OCR: every figure is typed, normalised and cited back to its source page.
How accurate is the extraction?
Pulse delivers 97%+ word and 99%+ character OCR accuracy, and structured data extraction validated past 99% (99.21% element accuracy, 99.65% recall, 99.06% precision) on dense, ground-truthed assay data — versus the roughly 5% typically recovered by basic OCR.
Can it read handwritten, stamped, or Cyrillic Soviet-era documents?
Yes. Pulse combines computer vision, OCR and LLM-based extraction with statistical reconciliation to handle handwritten, stamped and degraded scans, including Russian and Cyrillic archives, with bilingual output that preserves the original layout and tables.
How is this different from uploading documents to ChatGPT?
A generic chatbot can't reliably answer from your documents, doesn't know mining terminology, can't cite sources and isn't private or auditable. Pulse builds a private, encrypted, domain-trained knowledge base where every answer is cited to a source page — accuracy you can put in front of an investment committee.
What languages and formats can Pulse handle?
Any format, in any language. Pulse ingests PDFs, images, maps, spreadsheets and scans, and lets you query and export in your language in real time.
What can Pulse ingest beyond my own archive?
The same engine continuously ingests public-market disclosure (filings, technical reports, drill results) and regional and government datasets — geochemical surveys, open-file drill-hole databases, and tenement and relinquished-ground reports — onboarded jurisdiction by jurisdiction.
How does the cost compare to digitising manually?
Building it in-house typically takes 18–24 months, three to five specialist hires and US$400,000–600,000. Pulse delivers at under a third of that cost and time — up to 70% cost saved and 12+ months faster — with one reviewer to sign off, not a new team.
Is my data secure and do I own it?
Yes. Each client runs in a dedicated, encrypted environment — your data, your boundary. Raw extraction sits in a holding layer until a human signs it off into your clean master dataset.
Talk to your archive.
Natural resources run on granular data. We automate that data — and the decisions it powers. Book a tailored walkthrough on your hardest documents.
Less searching. More strategising.™
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