Not a chatbot. Tools built for your work.
Professional services clients don't need a coding assistant or a general chat interface. They need tools that make core work faster and more profitable — built around their own documents, templates, and workflows, with AI that actually understands their business.
Where AI delivers the clearest return.
Legal work is document-intensive, precedent-driven, and billed by the hour. Every application below compresses work that currently takes days into hours — and produces work product that never left the firm's systems.
Find the issues across thousands of pages.
Upload an entire contract bundle. Ask: "Find every clause that creates liability exposure if the target misses an earn-out." Currently takes a team of associates weeks. With private AI on the firm's document library — hours. The billable time saving from a single transaction can justify the annual contract cost.
Draft from your templates. Flag counterparty deviations.
Draft NDAs, service agreements, and shareholder documents from the firm's own standard templates, adjusted for jurisdiction and context. Flag where counterparty redlines deviate from market standard. Done hundreds of times a year at every firm.
Transcribe, extract, open — automatically.
Transcribe client calls, extract key facts, run conflict checks against the matter register, and draft the matter opening. Paralegals spend significant time on this. The AI does not miss things.
Across the matter, the firm's precedents, and external sources.
Synthesise research across a matter's history, the firm's previous similar matters, and their precedent bank. The AI has read everything — it surfaces the relevant case, the relevant clause, the relevant memo.
Junior drafts. AI elevates to partner standard.
A junior associate's draft is reviewed and elevated by AI before going to the partner. Drafting time reduced by 60–80%. Partner's review time reduces accordingly. Output quality is consistent.
Observe the working day. Suggest the time entries.
Lawyers are notoriously poor at capturing time. The AI observes documents opened, emails sent, calls taken, and drafts time entries in billing-appropriate language at end of day. Recoverable time increases. Billing disputes decrease.
Client financial data handled where it belongs.
Mid-size accounting firms handle the most sensitive financial information their clients possess. Generic cloud AI is off the table. These applications run entirely on local infrastructure.
Flag inconsistencies and anomalies across an engagement.
AI reviews working papers for internal consistency, flags items that warrant attention, and cross-references figures against source documents. Audit review becomes faster; nothing slips through.
Draft letters and reports from your templates.
Management letters, tax computations, advisory reports — drafted from the firm's own formats using the client's own numbers. Partner reviews and signs off. First-draft time collapses.
Pull structured data from unstructured documents.
Extract figures, dates, and entities from contracts, bank statements, and board minutes without manual data entry. Feeds directly into working paper templates.
Answers grounded in current standards and the firm's own library.
Technical accounting queries answered against the firm's internal guidance, past technical memos, and current standards — without anything leaving the building.
Patient data that never leaves the clinic.
Healthcare clinics want AI for clinical documentation and admin automation but are unable to use cloud AI compliantly. This is one of the most underserved markets for private AI.
From consultation to structured note, automatically.
Transcribe consultations, extract diagnoses, medications, and follow-up actions, and produce a structured clinical note. Clinician reviews and approves. Documentation time cut substantially; note quality consistent.
Referral letters, discharge summaries, patient communications.
Standard correspondence drafted from clinical record data. Referral letters, discharge summaries, appointment reminders — produced in the clinic's format with the patient's actual information.
The same capability, applied to other sensitive domains.
Engineering & architecture
Specification review, drawing cross-reference, tender response drafting, project documentation summarisation. Design IP and client data stay inside the firm's systems.
Financial advisors
Suitability reports, portfolio commentary, client correspondence — drafted from the firm's own templates using the client's actual data. Regulatory-safe; no client data on US servers.
Manufacturing
Process documentation, specification comparison, supplier correspondence. Recipe, formula, and process IP built over decades stays within the company's systems.
Councils & public bodies
Planning application review, policy Q&A, resident correspondence, committee paper drafting. Large document volumes; staff time is the bottleneck. AI moves that bottleneck.
Housing associations
Tenancy document processing, maintenance correspondence, compliance documentation. Large organisations with extensive document processing requirements, and limited AI options that keep data local.
Private schools & universities
Student record processing, research document summarisation, administrative correspondence, HR documentation. Student data and research IP handled entirely on-site.
Your documents are the system's knowledge.
Every application we build uses retrieval-augmented generation: your entire document library — contracts, precedents, templates, past matters, manuals, policies — is indexed and made searchable by the AI. When a user asks a question or requests a draft, the system retrieves the most relevant documents from your own library and provides them as context.
The AI doesn't hallucinate a generic answer — it answers using your actual documents, your actual templates, in your specific language and format. A new file added to your library is searchable within minutes. No retraining required.
After 6–12 months of usage, when enough high-quality examples have accumulated, we can fine-tune the model on your firm's specific patterns — further specialising it to your style, your standards, your way of working. RAG first, fine-tune later with real data: technically sound and a compelling managed service story.