Dawloom

AI solutions

AI that ships to production and pays for itself. Built model-agnostic, so you're never locked in to one provider.

The toolbox

We work across every major AI provider and pick per project. The result: if a better or cheaper model appears next month, your product can use it without a rewrite.

OpenAI

GPT models, the Agents SDK for tool-using assistants, and the Realtime API for voice.

Anthropic

Claude models through the Claude API, plus the Claude Agent SDK for autonomous agents.

Google Gemini

The Gen AI SDK for Gemini models, strong at long context and multimodal input.

Vercel AI SDK

One TypeScript interface over every provider, with streaming UI, agents, and workflows.

OpenRouter

One API for hundreds of models, so switching providers is a config change, not a rewrite.

Model Context Protocol

The open standard that connects AI assistants to products and data, including yours.

Questions we actually get

Short answers, no sales language. If yours isn't here, ask an engineer directly.

Ask us anything
Which AI model will you use for my project?

The one that fits the job after we test against your real use case. We build with the OpenAI, Anthropic, and Google SDKs, and wire projects through the Vercel AI SDK or OpenRouter where it makes sense, so you can change models later without a rewrite.

What does an AI feature cost to run?

Model usage is billed per token by the provider, and costs vary hugely with design. We engineer for cost from day one: prompt caching, smaller models for routine steps, batching where latency allows. You get a cost estimate per feature before we build it.

Is our data used to train the models?

No. Commercial API traffic from OpenAI, Anthropic, and Google is not used for training by default. Where requirements are stricter we can add zero-retention agreements or route sensitive steps to models you host.

Do we actually need AI?

Sometimes no, and we'll say so. If a script, a database query, or a form solves the problem, that's what we recommend. AI earns its place when the input is messy human language, documents, or judgment calls at scale.

Got something to build?

Tell us what you need. An engineer replies, not a sales team.

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