AI & Automation
Automate the work. Amplify the team.
We build custom AI systems and workflow automations that eliminate repetitive operations, surface intelligent insights, and let your team focus on work that actually requires human judgment.
15+
Automation Projects
60%
Avg Ops Time Saved
48 hrs
Avg Proof-of-Concept
What is Included
Everything you need,
delivered.
LLM-Powered Feature Development
Custom GPT-4o, Claude, or Gemini integrations — RAG pipelines, structured output, tool calling, and prompt engineering done properly.
Intelligent Document Processing
Invoice extraction, contract analysis, report summarization — OCR plus LLM for documents that need to be read, not just parsed.
End-to-End Workflow Automation
n8n, Zapier, and custom webhook pipelines that connect your SaaS tools and eliminate manual data handoffs between systems.
AI-Powered Search & Discovery
Semantic search with Pinecone, Weaviate, or pgvector. Find what users mean, not just what they typed.
Conversational AI Interfaces
Internal copilots, customer-facing chatbots, and AI assistants with memory, tool use, and escalation logic.
Data Pipeline & ETL Automation
Automated data ingestion, transformation, and delivery — from API sources to warehouses to dashboards.
Monitoring & Observability for AI
LLM cost tracking, latency monitoring, prompt failure alerts, and output quality scoring in production.
Human-in-the-Loop Workflows
Hybrid automation with review queues for edge cases. AI handles the 90%, humans handle the 10% that matters.
Our Approach
How we get
it done.
Process Audit & Opportunity Map
We spend time in your operations to identify which processes are high-volume, rule-bound, and ripe for automation.
48-Hour Proof of Concept
Before committing to a full build, we prototype the highest-value automation to prove feasibility and ROI potential.
Data & Integration Assessment
We map your data sources, API availability, and access credentials. Integration complexity is scoped before building begins.
Pipeline Development & Testing
We build in stages: data extraction, transformation, AI processing, and output delivery — tested at each step with real data.
Monitoring & Alerting Setup
Every automation ships with alerts, error logging, and a dashboard so your team knows when something needs attention.
Handoff & Team Enablement
Documentation, runbooks, and a training session so your ops team can monitor, modify, and extend the automations themselves.
Real-World Examples
What this looks like
in practice.
Built an invoice processing automation for a logistics company — 3,000 invoices/month processed in minutes instead of days, saving 40 hrs/week of manual work.
Deployed an internal knowledge base copilot for an enterprise — engineers find answers in seconds instead of searching Confluence for 20 minutes.
Automated a client onboarding workflow for a B2B SaaS — 14-step manual process reduced to 2 human touchpoints.
Built a contract review AI for a legal services firm — first-pass review time cut from 4 hours to 12 minutes per contract.
Tech Stack
FAQ