Building Software for a Better World

We are a social enterprise that builds software for social impact organizations.

Our Mission

We are a social enterprise dedicated to building software for a better world. We partner with social impact organizations to create custom software solutions that help them achieve their missions. Our team of experienced developers is passionate about using technology for good, and we believe that software can be a powerful tool for positive change.

Our Services

Web Development

We build beautiful, responsive, and performant websites that are tailored to your needs.

Mobile App Development

We create native and cross-platform mobile apps for iOS and Android.

Software Consulting

We provide expert advice and guidance to help you make the right technology decisions.

Latest Blog Posts

Structured Outputs: JSON Schema Validation for LLMs

Ask an LLM for JSON and you will get broken JSON. Learn to constrain generation with Gemini response_schema and Pydantic, then verify the output as an explicit, catchable step.

Streaming Inference with FastAPI and Server-Sent Events

Turn a blocking LLM call into an incremental, observable stream of tokens with FastAPI StreamingResponse and Server-Sent Events — including cancellation and backpressure.

Secure AI Development: Secrets Management and Prompt Injection Defense

Instructions and data share the same token stream. Build the defensive stack for AI apps: env-based secrets, system-instruction hygiene, provider safety filters, output validation, and least-privilege tooling.

RAG Evaluation: Measuring Retrieval Quality Objectively

A RAG pipeline fails in two halves: retrieval and generation. Build a transparent Python eval harness computing hit_rate, MRR, context precision/recall, and faithfulness to know exactly which half to fix.

Observability for Agents: Tracing Tool Calls and Reasoning

An agent is a loop, not a single API call. Instrument it with OpenTelemetry AGENT/LLM/TOOL spans and a shared trace_id so you can attribute bad reasoning, slow dependencies, and tool failures.

MLOps for LLMs: Versioning Prompts, Data, and Weights

LLM apps drift for reasons unrelated to weights. Version prompts, datasets, and models against the metrics that decide whether a change is an improvement, using MLflow tracking plus the Model Registry.