Our documents have no consistent layout. Does that break extraction?

That is the case this is built for. Template and regex approaches break on every new layout; schema-driven extraction with an OCR fallback handles variation, and confidence scoring tells you where it was unsure.

How do we know an extracted value is correct?

Every field carries a confidence score, and low-confidence values route to a review dashboard before approval. The point is that you never have to trust the output blindly.

Can this plug into automation we already run?

Yes. DocExtract was built specifically to finalise an existing n8n pipeline rather than replace it, and integration at that level is the normal pattern.

Corporate and SaaS

Document intelligence, internal dashboards and drop-in AI features — engineered to slot into your existing product and processes.

Overview

AI and systems for corporate & SaaS teams

Document intelligence, internal dashboards and drop-in AI features — engineered to slot into your existing product and processes.

The document problem is universal and nobody budgets for it. Contracts, invoices, reports and forms arrive as PDFs and scans; somebody re-keys them; the errors surface a quarter later in a reconciliation. Meanwhile the knowledge needed to answer a customer question sits in a folder nobody can search.

We build both halves: extraction that turns unstructured documents into structured records with confidence scoring, so you know which values to trust, and retrieval that answers from your own documents with something you can check rather than a plausible-sounding summary.

Common challenges

Thousands of multi-format documents with no compliant way to search them
Internal tooling built ad hoc, with no single technology overview
Product teams wanting AI features without a rewrite

What we build

Types of solutions we provide

Capabilities we've applied specifically to Corporate and SaaS.

Document Intelligence
Hybrid-search RAG with PII detection and compliance-ready output.
Internal Dashboards
Deployment KPIs, infra metrics and live system health in one view.
In-Product AI
Branded assistants and smart search embedded in your product.
Automation Hooks
AI triggers wired to your existing webhooks and APIs.

Relevant services

Service families used in this sector

AI & Machine Learning
Agents, generative pipelines and vision/document models that read, reason and act on your data — not demos, production systems.
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Business Software & Portals
The internal systems that run day-to-day operations — booking, attendance, inventory and the portals your staff actually use.
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Data, BI & Dashboards
Dashboards leadership actually opens — Power BI, Tableau and custom builds, refreshed automatically and trusted by everyone who reads them.
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Automation & Integrations
The unglamorous work that pays for itself — connecting the tools you already run and deleting the copy-paste between them.
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Related work

Verified Corporate and SaaS projects

DocExtract
Self-hosted PDF data extraction platform — schema-driven LLM extraction with OCR fallback, per-field confidence scoring and human-in-the-loop review, built to plug into an existing n8n pipeline.
VoiceDeskAI
Inbound AI voice agent that answers business calls and books, reschedules or cancels appointments against real availability — Google Calendar sync, CRM integration and call transcription, multi-tenant across business types.
GeoAttend
Attendance management platform, delivered to multiple organisations with configuration customised to each one's needs.
View Project
Intelligent Document Processing
RAG system with hybrid search across thousands of multi-format documents, including PII detection and compliance-ready output.
Technology Dashboard
End-to-end tech stack overview with deployment KPIs, infra metrics and live system health indicators across services.

See all work

What you get

What a Corporate and SaaS engagement delivers

Built to this sector's constraints, then handed over. Code, infrastructure and accounts are delivered to you — no proprietary lock-in, no hostage licensing.

Get free consultation

Schema-driven extraction with OCR fallback for scanned input
Per-field confidence scoring, so low-confidence values get reviewed
Human-in-the-loop review before anything is approved
Hybrid search across multi-format document sets
Self-hosted deployment where documents cannot leave your environment

Questions