Discovery
We interview your team, audit your systems and data, and identify the workflows where AI can produce measurable savings. You get a clear picture of what is feasible now and what needs groundwork first.


Every organization is being told to “do something with AI.” The useful version of that starts with specifics: which workflows cost your team the most time, where your data actually lives, what your people will trust, and what oversight your industry demands. Our AI consulting engagements answer those questions and turn them into a roadmap you can execute.
Because Braid is an engineering-led agency, the consulting connects directly to delivery. The team that maps your workflows and writes your roadmap has shipped production software for higher-education, government, and venture-backed startups for over a decade, and builds custom domain-specific AI agents that run in production today.

Consulting is also how our Custom AI Agent Development engagements begin. Discovery identifies the workflows worth automating, the roadmap sequences them, and prototypes prove value before you commit to a full build. When the plan calls for a bespoke product, our Digital Innovation practice takes it from there.
What are Domain-Specific Agents?
Everybody is trying to build their own custom agents, and most of them stall, because piling more tools and more context onto one giant assistant eventually breaks down. The answer is composition: small, focused agents, each an expert in one domain, working together the way a real team does. That’s how we build, and Braid co-founder Justin Schroeder made the case at the AI Engineer World’s Fair.
We interview your team, audit your systems and data, and identify the workflows where AI can produce measurable savings. You get a clear picture of what is feasible now and what needs groundwork first.
A sequenced plan with costs, dependencies, and expected returns for each initiative, so your leadership can approve one phase at a time with full visibility into what comes next.
We document how work actually moves through your organization: the handoffs, the spreadsheets, the approvals, and the exceptions. That map determines where automation will hold up in daily use.
Clear policies for data access, model selection, human review, and auditability, so your AI systems meet the standards your industry and your customers expect.
Working proofs of concept on your real data, scoped in weeks. A prototype answers the feasibility question with evidence and gives stakeholders something concrete to react to.
When a roadmap item is approved, the same team builds, deploys, and monitors it. Keeping strategy and engineering under one roof keeps the plan honest about what production requires.
Our Custom AI Agent Development practice is where consulting recommendations become production systems. Discovery and workflow mapping identify the agents worth building, governance defines their guardrails, and our engineers then build small, domain-specific agents with precise tools and the telemetry to show exactly what happened on every turn. For a recent example, read how we built Bod.Coach, an AI personal trainer that coaches entirely over text.