AI agents & AI-driven development.
We use AI agents to accelerate our own development process u2014 and we build AI agents into our clientsu2019 applications. This dual expertise means we understand AI capabilities and limitations from daily production use, not just demos.
AI on both sides of the equation.
Most agencies talk about AI. We live it u2014 on both sides: we use AI agents to accelerate our own development process, and we build AI agents into our clientsu2019 applications. This dual expertise means we understand AI capabilities and limitations from daily production use, not just demos.
Boilerplate generation
Models, serializers, views, and tests scaffolded automatically.
Code review assistance
AI-powered code analysis for bugs, security issues, and optimizations.
Test generation
Unit and integration tests written alongside implementation.
Documentation
API docs, inline comments, and README generation.
What We Build with AI
Autonomous agents, retrieval pipelines, and intelligent automation u2014 integrated with your existing systems.
Custom AI agents
Autonomous agents that execute multi-step business workflows: document processing with extraction, classification, and routing; customer support triage, response drafting, and escalation; automated insight generation from structured and unstructured data; and domain-specific code generation for internal tools.
RAG pipelines
Connect large language models to your proprietary data u2014 knowledge bases you can search and query, AI-powered insights from CRM, support tickets, and usage data, and automated document review and policy checking for compliance.
Our AI Technology Stack
The layers we build on, from frameworks to monitoring.
| Layer | Technologies | |||||
|---|---|---|---|---|---|---|
| Frameworks | LangChain, LlamaIndex, CrewAInLLM providers | OpenAI, Anthropic, Mistral, open-source (Llama, Mixtral)nVector databases | Pinecone, Weaviate, pgvectornML libraries | scikit-learn, pandas, NumPy, Hugging Face TransformersnOrchestration | Celery, Redis, Kubernetes jobsnMonitoring | LangSmith, custom dashboards, Prometheus |
Production AI, not demos
Every AI system we deliver ships with the disciplines that keep it trustworthy.
Observability
Token usage, latency, accuracy, and cost tracking.
Guardrails
Input validation, output filtering, and hallucination detection.
Fallbacks
Graceful degradation when confidence is low.
Build with AI.
Describe the process you want to improve u2014 a senior engineer will map where agents fit, where RAG fits, and where something simpler wins.