Practical AI that ships to production: measurable, secure and wired into the systems you already run.
We find the repetitive, manual work in your business — copying data between systems, reading documents, writing reports — and build software that does it for you using AI. Your team spends less time on busywork and more on the work that needs people.
Overview
We add AI where it removes real work: reading invoices and contracts, classifying requests, summarizing long threads, generating reports, or giving your app search that understands meaning, not just keywords.
Our focus is production engineering — background jobs and queues for long-running AI tasks, cost and latency controls, fallbacks between model providers, observability and evaluation so quality doesn't silently drift.
Whether you're adding a first AI feature to an existing product or building an AI-native application, we take it from idea to a reliable system your team can own.
What's included
Extract structured data from invoices, receipts, contracts, forms and emails — validated and pushed into your ERP, CRM or database.
Summaries, smart replies, content generation, classification and recommendations, designed into your existing UX.
Search across products, documents or tickets by meaning, with hybrid keyword + vector ranking and filters.
AI steps inside business processes — triage, routing, approvals, report generation and bulk processing — with humans in the loop.
Model gateway, prompt management, usage and cost tracking, caching and provider fallbacks shared across features.
Test sets, automated scoring and production tracing so you can change prompts or models with confidence.
Use cases
Invoice capture, expense categorization and reconciliation support.
Contract clause extraction, comparison and risk summaries.
Automated reports, demand notes and exception handling.
Ticket triage, sentiment tagging and response drafting.
Process
Identify the highest-value, lowest-risk tasks for AI and define how we'll measure success.
Run the approach on your real data and compare against a baseline before building further.
Queues, APIs, UI, security, cost controls and monitoring — built to the same standard as the rest of your stack.
Documentation, dashboards and training for your team, then iterate on the next opportunity.
FAQ
Usually not. Modern models work well with your existing documents and a small set of examples. We check data quality early in the proof of value.
By choosing the right model per task, caching, batching, limiting context size and tracking spend per feature, with alerts before budgets are hit.
Yes. Integrating with existing systems through APIs, databases or file exchanges is a core part of what we do.
Share a few details and any documents — we'll reply within one business day with next steps.
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