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Case Studies

Real problems, real solutions.

From compliance automation to contract intelligence, see how organizations have turned fragmented workflows into auditable, repeatable systems.

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Compliance Workflow Automation

Financial Services / Legal Tech & Compliance

Delivered

Context

A compliance operations team at a fintech company ran a mature, well-documented process across five disconnected systems: a ticketing tool for change request intake, a project management platform for external submissions, a CRM for complaint tracking, a document storage system, and spreadsheets for issue tracking and reporting. The workflow functioned — but only because one person held the entire process in her head. There was no unified audit trail, no automated reporting, and no structural resilience if that person was unavailable.

Approach

Mapped the full compliance lifecycle across all five systems to identify where data was being manually copied, where linkages were inconsistent, and where audit artifacts had to be reconstructed after the fact rather than generated in real time. Designed a lightweight control layer to sit between the existing tools and the organization’s reporting obligations — connecting intake, review, external submission, and approval tracking without replacing any of the underlying systems. The first deliverable was a unified change record: one view of the full lifecycle from intake to post-launch monitoring, with an automatically generated audit trail.

Outcome

Process went from one person’s institutional knowledge to a system any team member could operate. Compliance workflows became auditable by design rather than by reconstruction. The same pattern was then extended to issue tracking and complaint management.

Multi-Document Contract Validation

ERP / SaaS / Distribution

Delivered

Context

A software company’s contracts team was manually comparing three document types for every new customer transaction: the CRM opportunity record, the order form, and the purchase order. Discrepancies between these documents — mismatched pricing, incorrect quantities, wrong contract terms — were caught inconsistently and required senior review of every contract regardless of complexity.

Approach

Built a hosted validation service that automated the comparison end-to-end. The service accepted the CRM opportunity data and the attached order documents, extracted the relevant fields from each, and ran them against the organization’s existing validation ruleset — including non-obvious rules like monthly-to-annual pricing conversions and line-item status logic for upgrades. Results were written back directly into the existing CRM record, so the contracts team never left their current workflow.

Outcome

Contracts team shifted from reviewing every contract to working exceptions only. Validation coverage extended to both new customer and upgrade/add-on scenarios from day one. The organization’s institutional knowledge about contract rules was codified into a repeatable, auditable system.

Insurance Document Comparison

Insurance

Delivered

Context

A large insurance organization needed to accelerate two distinct but related document-intensive workflows: reviewing redlined contract versions during negotiations, and comparing policy coverage language against submitted claims. Both tasks required a senior analyst to read and cross-reference long, dense documents — work that was accurate but slow, and created bottlenecks during high-volume periods.

Approach

Applied NLP-based document analysis to both workflows. For contract redlines: built a system to identify and surface meaningful changes between document versions, filtering out formatting noise and flagging substantive edits for human review. For coverage/claims comparison: built a pipeline to extract the relevant coverage provisions from policy documents and map them against the specific circumstances described in claims, surfacing coverage applicability and potential gaps.

Outcome

Reduced analyst time on document review by shifting effort from reading to decision-making. High-volume periods no longer created backlogs in either workflow. The organization gained consistency in how documents were reviewed and a structured record of what was compared and flagged.

Contract Intelligence with Gold Standard Versioning

Legal Tech / Contract Management

Delivered

Context

A legal technology company was building a contract review product for enterprise clients who needed to compare incoming contract language against their own approved “gold standard” clauses. The core challenge was not just identifying differences between a proposed clause and the gold standard, but doing so in a way that was version-controlled, auditable, and useful to legal teams who needed to understand why a clause deviated, not just that it did.

Approach

Led product development on the contract intelligence layer, including the Q&A and negotiation review workflows. Designed the gold standard comparison architecture to surface proposed redlines alongside the current clause and the approved baseline, giving reviewers a three-way view. Worked through LLM behavior issues where the model conflated adjacent clause types — identifying these as context and prompt-level issues requiring targeted fixes before client-facing demos.

Outcome

Delivered a functioning negotiation review product with a split-pane interface that legal teams could use to evaluate proposed changes against gold standard language. Established a version-controlled clause comparison workflow that gave enterprise clients an auditable record of what was accepted, rejected, or escalated during contract negotiations.

Regulatory Data Automation — Market Intelligence Pipeline

Telecommunications

Delivered

Context

A Brazilian market intelligence firm produced client reports, due diligence packages, and strategic analyses of the broadband and mobile telecommunications market. Their process required manually downloading regulatory data from the national telecommunications agency, cleaning it, and running calculations through Excel macros. The process was slow, error-prone, and meant clients were receiving analysis built on data that could be weeks or months old.

Approach

Built an automated pipeline to ingest broadband and mobile access data from the regulatory source on a continuous basis, replacing the manual download-and-macro workflow with programmatic processing. The pipeline handled the data cleaning, transformation, and calculation logic that had previously been embedded in spreadsheets, and produced outputs structured for direct use in client deliverables.

Outcome

Eliminated the manual data preparation cycle. Client reports, due diligence packages, and strategic recommendations were built on current data rather than last month’s spreadsheet. Analysis that previously required hours of manual preparation became available on demand.

AI Readiness Scoping — Healthcare Clinic

Healthcare

Delivered

Context

A healthcare clinic with investor backing was exploring AI implementation but had not yet defined its highest-priority use case. The problem space was open — potential directions ranged from computer vision on clinical imaging to operational workflow automation — but the clinic needed a structured process to evaluate options before committing to a technical direction.

Approach

Scoped and designed a two-phase engagement: a discovery phase to surface current-state workflows, data environment, regulatory constraints (HIPAA, FDA SaMD guidance), and candidate use cases; followed by an alpha phase to deliver an architecture specification, technical design document, and proof-of-concept for the highest-priority use case identified in discovery. Produced a full SOW defining deliverables, acceptance criteria, and the decision gate between phases.

Outcome

Delivered a structured framework for AI use case prioritization in a regulated clinical environment. The phased approach gave the client a clear decision point before committing development resources, and ensured regulatory considerations were embedded from the start rather than retrofitted.

Insurance Document Processing Automation

Insurance

In Scoping

Context

A public adjuster firm was processing insurance claims through a heavily manual workflow: transcribing information from inspection reports, reading and summarizing lengthy adjuster documents, and manually scheduling follow-ups based on what was found. The process was time-consuming, inconsistent across adjusters, and created delays in moving claims forward.

Approach

Proposed an AI-powered document processing pipeline to replace the manual transcription and summarization steps. The approach: break incoming adjuster documents into structured chunks with specific extraction targets (e.g., wind/hail damage percentages by carrier, verification sources, coverage flags), run AI summarization against each chunk, and surface decision-support outputs that adjusters could act on directly.

Outcome

Engagement in scoping phase at time of documentation. Scope and timing under development.

Field Service & CRM Optimization

Construction / Field Services

In Scoping

Context

A roofing company was converting leads at a low rate — roughly 19 closed jobs from 200 leads — and was constrained to one crew despite having demand for three. The company lacked a data-driven approach to lead prioritization, territory planning, or crew assignment.

Approach

Designed a CRM and workflow optimization strategy using hail storm integration to auto-target existing clients and canvas new prospects in affected areas, satellite imagery to identify high-probability homes, and a follow-up cadence aligned to insurance claim windows. Included crew scaling framework and territory-based assignment logic.

Outcome

Engagement in scoping phase at time of documentation.

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