LegalTech
LegalTech Software Development — Contract Lifecycle, Legal AI, eDiscovery & Matter Management
LegalTech is being rewritten by AI faster than the bar associations can write rules about it. We build legal AI products with source attribution, hallucination guardrails, and confidentiality architecture that holds up under privilege review.
What we hear from LegalTech teams
- Legal-AI features that hallucinate confidently — and the moment a wrong citation reaches a client, the product is unusable
- Contract data fragmented across DMS, email, Word docs, and signed PDFs — nothing is queryable as data
- eDiscovery scaling problems: the volume tripled, the budget didn't
- Vendor AI tools that touch privileged matter data with unclear sub-processor chains
- Document-source attribution that lawyers actually trust — most products fail this bar
- Matter-management systems that recreated the old timekeeping UI and call it modernisation
Regulation & compliance we work with
ABA Model Rule 1.6 (confidentiality) + state-bar equivalents
Attorney-client privilege protection across AI pipelines
GDPR + EU AI Act (high-risk classification considerations for legal AI)
SOC 2 Type II — table stakes for selling to AmLaw / corporate legal
ISO 27001, HIPAA where healthcare-litigation data flows through
Data-residency requirements per matter / per client
What we deliver
Legal AI assistants with retrieval-grounded answers, full source attribution, and explicit 'I don't know' behaviour
Contract lifecycle (CLM) platforms: drafting, redlining workflows, clause libraries, obligation tracking
eDiscovery platforms: ingestion, processing, review, production — with TAR/CAL integration where appropriate
Matter-management systems built around how legal teams actually work, not how billing wants them to
DMS + email + chat integrations (NetDocs, iManage, Microsoft 365, Slack)
Privilege-aware data pipelines: matter walls, ethical screens, sub-processor minimisation
Evaluation harnesses for legal AI — citation accuracy, hallucination rate, scope adherence
FAQ
- How do you prevent legal AI from hallucinating?
- Three layers. First, retrieval grounding — answers cite specific clauses or paragraphs from the matter's documents, not the model's training. Second, refusal behaviour — the system says 'I don't know' rather than confabulating when retrieval comes up empty. Third, an evaluation harness that runs continuously on a labelled set of matter questions, so regressions are caught before deployment. There's no silver bullet here; it's discipline applied at every layer.
- Are you familiar with bar confidentiality rules and how they affect product design?
- Yes — they shape the architecture, not the wrapper. Matter-data segregation, sub-processor minimisation, prompt-and-response logging policies, model-provider DPAs, and per-matter access controls are all design decisions, not features. We'll work with your GC / ethics counsel to map the rules to the system, but we won't render bar-compliance opinions.
- Can you integrate with iManage, NetDocs, or other document management systems?
- Yes. The DMS is usually the system of record; the LegalTech product is a layer on top. We've shipped integrations against iManage Work / Cloud, NetDocuments, SharePoint, and Box-as-DMS configurations. The work is mostly in respecting matter walls and ethical screens correctly, not in the API itself.
- What about the EU AI Act?
- Most legal AI use cases tied to consequential decisions (employment, immigration, biometric ID in legal contexts) are likely high-risk under the EU AI Act, with the corresponding documentation, transparency, and human-oversight obligations. We'll surface that classification question in scoping and design for the high-risk obligations from day one if your product is likely to land there.