AI solutions for
We build production AI systems. Proper architecture, evaluation, integrations, and infrastructure from day one.
Start with the problem. Design the system. Measure it. Ship it.
User Request
App Trigger
AI App
Guardrails
LLM / Model
Orchestration
Agent
Reasoning
RAG & Vector
Retrieval
Tools & APIs
Functions
Evaluations
Metrics
Production
Monitoring
ENGINEERING PHILOSOPHY
AI is easy to demo. Production AI is different.
A production AI system requires more than calling an LLM API. It needs guardrails, evaluation, data context, security, and continuous telemetry.
Prototype vs Production
Direct API calls break in production. Engineered systems don't.
Demo vs Reliable System
80% demo accuracy is easy. Production reliability requires evaluation.
Model vs Product
A model isn't a product. Products connect to real data and workflows.
Feature vs System
AI features call prompts. AI systems combine models, retrieval, agents, and infra.
ENGINEERING CAPABILITIES
We don't just build AI features. We engineer AI systems.
Whether starting from scratch or integrating into existing products, we deliver production-ready solutions.
AI Applications & Copilots
End-to-end AI products built for real users, not demos.
AI Agents
Agents that reason, use tools, and complete multi-step tasks reliably.
RAG & Knowledge Systems
Retrieval systems that actually find the right thing.
AI Integrations
AI connected to the systems your business already runs.
AI Workflow Automation
Replace manual processes with AI that understands context.
AI System Architecture
The right model and infra for your use case.
If you can't measure your AI system, you can't reliably improve it.
AI is probabilistic. Evaluation is not optional. It is how you know the system works.
AI INTEGRATIONS
AI shouldn't live in isolation.
The most useful AI connects to the data and tools your business already runs on.
Summarize sales calls, extract action items, and sync structured notes directly into HubSpot or Salesforce.
Input
Output
Already have a product? Make it intelligent.
You don't always need to rebuild your system. AI can often be integrated into your existing product and infrastructure to deliver immediate value.
AI Assistant & Copilot
Context-aware sidekick embedded inside your web app UI.
Semantic Search
Replace keyword search with vector meaning search across user data.
Document Intelligence
Automate document parsing, invoice extraction, and PDF summaries.
Natural Language Analytics
Convert user text queries directly into database charts and reports.
AI Customer Support
Deflect routine tickets with grounded RAG knowledge.
Process Automation
Background workflows that decision-route data automatically.
SYSTEM ARCHITECTURE
We design the system behind the AI.
Every production AI system needs more than a model. Here is what we build around it.
Selected AI work built around real problems.
High-level architectural breakdowns showing business problem, engineered solution, and outcome metrics.
Internal Knowledge Assistant
Teams spend hours searching scattered docs, wikis, and PDFs for answers that should take seconds.
RAG pipeline built with LangChain hybrid retrieval, reranking, and citation grounding to prevent hallucinated answers.
Tier-1 Support Agent
High ticket volume for routine requests. Support teams stuck on the same handful of issues.
LangChain / LangGraph tool-calling agent with access to order systems and policy docs. Human escalation built in.
Sales Call Intelligence
Sales managers had no visibility into call quality. Reps were manually writing notes after every call, which nobody read.
Pipeline that transcribes calls, extracts action items, scores sentiment, and pushes a structured summary directly into the CRM.
Contract Review Assistant
Legal and ops teams were reading every contract manually to flag non-standard clauses. It was slow and missed things.
Document ingestion pipeline with clause extraction, a risk-scoring model, and a review UI that surfaces only the sections that need human attention.
Natural Language Analytics
Non-technical stakeholders had to wait for data analysts to pull reports. Simple questions took days to get answers.
Natural language interface over a SQL database with schema guardrails, query validation, and chart generation. Analysts still own the data model.
We would love to help you build something.
You have a business problem, a workflow that doesn't scale, or an idea you want to explore with AI.
Tell us what you're trying to achieve. We'll design, evaluate, and ship the right solution.
MODEL AGNOSTIC ARCHITECTURE
Modern AI engineering, without vendor lock-in.
Technology choices are based on system requirements. We select optimal models, vector databases, and infrastructure for accuracy and cost goals.
Models
Multi-Model StrategyEngineering & RAG
RAG is not deadEvaluation & Stack
Production ReliabilityYou don't need to know what technology you need.
Tell me what you're trying to achieve. I'll figure out the right technical approach.
Talk to an AI EngineerHIGH-LEVEL DISCOVERY FRAMEWORK
Not sure where AI fits? Start with the problem.
Understand the Problem
What's the friction? What data exists?
Find AI Opportunities
Where does AI actually help?
Check Feasibility
Cost, latency, accuracy tradeoffs.
Design the System
Model, retrieval, agents, infra.
Build and Measure
Ship iteratively with evals.
Ship to Production
Monitor, measure, improve.
Let's build something useful with AI.
Have an AI idea, an existing product, a business problem, or a system that needs improvement? Tell me what you're trying to achieve and let's figure out the right solution.
No technical specification required.
Talk to an AI Engineer
Tell me what you're building or what problem you're trying to solve. No technical specification required.