Contracts, support tickets, regulatory filings, internal docs — your enterprise sits on massive volumes of text that nobody has time to read. We build NLP systems that extract, classify, and act on that information automatically.
Discuss your NLP challengeEnterprise teams generate thousands of documents daily. Legal reviews contracts manually. Compliance reads regulatory updates line by line. Support teams categorise tickets by hand. The information is there — extraction just isn't scalable with humans. Generic LLM APIs don't understand your domain terminology, your document formats, or your compliance requirements. Custom NLP systems do.
Automated extraction from contracts, invoices, regulatory filings, and internal reports. We build systems that understand your specific document types — not generic OCR that dumps text, but structured extraction that pulls out the fields, clauses, and data points you actually need. Output goes directly into your existing systems via API.
Customer-facing chatbots and internal knowledge assistants that actually work. We build multi-turn dialogue systems grounded in your data, with fallback to human agents when confidence is low. Every response includes source attribution so users can verify answers. No hallucination-prone black boxes.
Retrieval-augmented generation connects large language models to your proprietary data. Your legal team asks a question in plain English, the system searches your document corpus, and returns an accurate answer with citations pointing to the specific source documents. We handle chunking strategy, embedding model selection, retrieval ranking, and answer generation.
Sentiment analysis across millions of customer interactions. Topic modelling across your entire support ticket history. Entity extraction from regulatory filings. These aren't one-off analyses — they're production systems that run continuously and feed insights into your dashboards and workflows.
We don't do web apps on the side. Every engineer on your project has deep AI specialisation and has deployed production ML systems before.
We don't implement the first architecture that works. We explore options, test assumptions, and design the solution that fits your specific constraints — even if it means building something nobody's built before.
Our AI-augmented methodology compresses delivery timelines by 2-3x compared to traditional consulting. Not by cutting corners — by using AI for the volume work while senior engineers focus on decisions that matter.
Timeline
6-10 weeks from kickoff to production
Team
2 senior NLP engineers + 1 data engineer
Deliverables
Production NLP system, API endpoints, evaluation framework, user documentation, integration with your existing systems
After launch
Optional retainer for model updates as your document types or terminology evolve
A compliance team at a financial services firm needed to review 12,000+ vendor contracts annually for regulatory risk clauses. Six full-time analysts spent 80% of their time on initial review, leaving minimal capacity for the complex edge cases that actually required human judgment. We built a document intelligence system that ingests contracts in any format, extracts key clauses, flags high-risk language against a configurable rule set, and routes only genuine exceptions to human reviewers. The system processes a contract in under 30 seconds. The compliance team now spends 90% of their time on judgment calls, not document scanning.
Representative of a typical engagement.
All processing can run on-premise or in your private cloud. Documents never leave your infrastructure. We design architectures that comply with SOC2, HIPAA, GDPR, and industry-specific regulations. For clients in regulated industries, we provide architecture documentation for your compliance team to review before any data touches the system.
Yes. We build API-first systems that integrate with whatever you're running — SharePoint, Confluence, custom DMS, S3, or any system that can send documents via API. We scope the integration during the first two weeks so there are no surprises.
Modern NLP models support 100+ languages. For enterprise use cases, we fine-tune on your specific language, domain terminology, and document formats. If you operate in multiple languages, we build systems that handle them all with consistent accuracy.
It depends on the document type and complexity, which is why we always establish accuracy benchmarks early. For structured documents like invoices and forms, we typically achieve 95%+ accuracy. For complex legal or regulatory text, accuracy is lower on edge cases — which is why we design human-in-the-loop workflows where the system handles the volume and flags exceptions for expert review.
Tell us about your document types and volume. We'll show you what's automatable and what returns you can expect.
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