We are an AI-first technology and consulting practice. We deploy at the client, building AI systems that operate inside real products with measurable operational impact.
Write to hello@21xventures.com
Based in Brazil · open to global conversations
A focused practice for production AI.
21xVentures is an AI-first technology and consulting practice based in Brazil. We help founders and teams turn AI opportunities into software, operating routines, and decision systems that can be used in production.
Examples of the work include operational workflows where AI consolidates routines spread across spreadsheets, CRM, and messaging; back-office processes where deterministic code handles most steps and the model contributes only where generation adds value; and decision-support systems graded at each reasoning checkpoint before they reach production.
To explore a project, write to hello@21xventures.com
Practice
One signature, from audit to operation.
Three phases, one continuous engagement. We audit the workflow, design the evals, and ship the system that operates inside the team.
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Phase 01 Audit
The engagement opens with a workflow audit before any code is written.
We work alongside the team to map the actual workflow. From there, we identify which steps benefit from AI, which require deterministic code, and which depend on human judgment. With this distinction in hand, implementation decisions follow from observed reality, not from assumptions about it.
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Phase 02 Evals
Evaluation grades the reasoning at each checkpoint, not only the final output.
We build the evaluation pipeline from a small golden dataset, structured to grade the agent at each step of the reasoning it reproduces. With this approach, regressions surface at the checkpoint where they originate, which makes the system observable rather than opaque.
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Phase 03 Deployment
Deployment begins with the smallest viable unit of autonomy and expands incrementally.
Implementation runs through APIs layered over the existing stack, without data migrations. The agent operates first in a sandbox; the smallest unit of autonomy that delivers measurable value is then released to production. From there, additional capability is composed over time on the basis of observed performance.
Notes from the work.
Brief notes on AI systems, product decisions, and what we learn in practice. Written when there is something specific to say.
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The Demo Trap
Three types of AI demos, four common failure modes, and the test that separates convincing demos from production-ready ones.
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When Your Eval Set Stops Telling the Truth
Four ways evaluation sets drift, the quarterly audit that catches it, and the discipline of retiring examples.
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Latency Budgets for AI Features
A practical latency budget for AI features, and the four levers to use when the system is over the limit.