Finance

Prospecting, sales workflows, third-party data

ProspectingSales workflowsData pipelinesThird-party enrichmentDocument processing

Incomplete data, brittle handoffs, and compliance rules that rule out a lot of tooling. Reliability, auditability, and a data path security can defend are baseline here, not extras.

Common challenges

Stale or incomplete prospect data

Manual research and consolidation that waste rep time

Compliance constraints on tools and data sources

Siloed internal data slowing safe decisions

Document-heavy intake and research work

Experience

Prospect enrichment pipelines across multiple third-party sources

Sales workflow applications that surface the right leads at the right time

Document extraction and classification

Search across consolidated prospect data

Edge or in-environment processing when firm or client data has to stay put

SOC 2 and ISO 27001 architecture

Outcomes

Reps walking into calls with real context, not cold research

Enrichment that surfaces the right leads earlier

Controls over which data sources enter the workflow and how they move

Expertise in this space

Automation & Applied AI

Manual work mapped and measured, then automated where it pays off. Models chosen on evals and cost, with guardrails.

Platform & Infrastructure

AWS and GCP platforms defined in code. Kubernetes, GitOps delivery, observability, and cost control.

Data Engineering

Ingestion, enrichment, and event pipelines. Data modeled and accessible for products, analysis, and automation.

Product Engineering

Web, mobile, and backend products from first version through launch and iteration. Full stack, from data model to interface.