Autonomous
Intelligence.
Automate manual workflows with custom AI agents to exponentially increase efficiency and operational scalability.
System Deployment.
The goal is simple: eliminate manual friction. We deploy custom large language models (LLMs) and deterministic workflow logic to scale operations infinitely without adding headcount.
Custom AI Agents
We engineer highly specific autonomous agents designed to execute complex, multi-step tasks within your existing enterprise ecosystem without human supervision.
Workflow Automation
Connecting disparate software tools (CRM, ERP, Billing) via n8n or custom Python middleware to trigger automatic data transfer, completely removing manual entry bottlenecks.
AI Chatbots
Context-aware, LLM-powered interfaces trained exclusively on your proprietary documentation that resolve Tier 1 customer inquiries and qualify inbound leads instantly.
Business Process Automation
We don't just automate tasks; we automate departments. By mapping out high-level business logic, we deploy AI to handle data enrichment, reporting, and predictive analysis at scale.
Internal AI Assistants
Secure, internal copilots (RAG systems) trained on your company's historical data, Slack messages, and legal contracts to assist your workforce with instant knowledge retrieval.
LLM Integrations
Seamless API integrations with frontier models including OpenAI (GPT-4o), Anthropic (Claude 3.5), and open-source local models, embedded directly into your software stack.
Retrieval-Augmented Generation (RAG).
Generic AI hallucinates. Enterprise AI requires deterministic accuracy. We architect RAG pipelines that force the LLM to verify every output against your proprietary vector database before responding.
- Vectorization: Converting thousands of PDFs, CRM notes, and technical docs into mathematical embeddings stored in Pinecone or Milvus.
- Semantic Search: When queried, the system retrieves only mathematically relevant context, bypassing context-window limits.
- Grounded Synthesis: Anthropic Claude or GPT-4o processes the retrieved data to generate a perfectly accurate, hallucination-free response.
Implementation & Yield.
Contract Analysis Agent.
The Friction: Paralegals were spending 14 hours per week manually reviewing 50-page NDAs and vendor agreements to highlight non-standard liability clauses.
The Architecture: Deployed a custom RAG agent using Claude 3.5 Sonnet, specifically tuned on the firm's historical contract playbooks. Integrated via API directly into their Document Management System to flag anomalies upon upload.
Autonomous Tier-1 Support.
The Friction: Support tickets were scaling faster than revenue. Human agents were bogged down answering repetitive API integration queries, causing a 24-hour SLA breach.
The Architecture: Engineered an Intercom-integrated AI agent trained exclusively on their internal developer documentation and past resolved Zendesk tickets. Set strict guardrails to escalate complex issues to humans.
Automated Invoice Reconciliation.
The Friction: Accounting team was manually matching massive carrier shipping invoices (FedEx, UPS) against Shopify order data, resulting in $40k/mo in uncaptured discrepancies.
The Architecture: Built a Python-based automation workflow that utilizes Vision API to read messy PDF invoices, structures the data into JSON, cross-references Shopify's GraphQL API, and automatically flags mismatched weight charges in Slack.
AI Property Underwriting.
The Friction: Analysts spent days pulling zoning laws, demographic data, and historical comps before they could decide if a land parcel was worth acquiring.
The Architecture: Created an internal web app where analysts input an address. The backend triggers a cascade of API calls (Zillow, local county databases), feeds the raw data into GPT-4o to calculate preliminary yield, and outputs a formatted 10-page underwriting PDF.
Autonomous Client Reporting.
The Friction: Account managers spent the first week of every month manually pulling data from Google Ads, Meta, and HubSpot to build client presentations.
The Architecture: Deployed n8n automation to aggregate raw API data on the 1st of the month, pass the numerical data to an LLM to generate narrative "Insights & Next Steps", and push the final content directly into Google Slides templates.
Resume Parsing & Matching Logic.
The Friction: Recruiters were overwhelmed by 1,000+ inbound nurse applications daily, unable to quickly identify candidates with specific state licenses and ICU experience.
The Architecture: Intercepted the inbound application webhook. Passed PDF resumes through OCR and an LLM prompt engineered to extract 15 specific strict-typing data points. Auto-updated the ATS and instantly triggered SMS interviews to top 10% candidates.