Capability sprint
Prove the workflow, the risks, and the evaluation approach before committing to a full build.
AI agents
Agents for real workflows, with the guardrails included.
Agents that do a job inside your operation, and agents inside the products you already run. Evaluation, guardrails, and observability are part of the build, not an add-on.
The model is the smallest part of the system. What makes an agent useful in production is the work around it: the tools it can call, the data it can see, the checks on its output, and the evidence that it is doing the job. We build that part.
- Sheet
- 04 of 06
- Included
- eval harness, guardrails, tracing, cost controls
- Shapes
- workflow agents, support agents, agents inside existing products
- Output
- a system you can measure, not a demo
You might be here because.
Start from the constraint you have, not from a solution somebody already picked.
A workflow is repetitive but too nuanced for ordinary automation.
A prototype works in demos and fails unpredictably in production.
Customers or staff need reliable answers from private, changing knowledge.
Prompt changes cannot be tested safely before release.
Latency, cost, or the lack of observability is blocking adoption.
Human review and escalation paths are missing or unclear.
What changes
The system around the model.
The model is the smallest part. What makes an agent useful in production is the work around it, and that is what we build.
- The tools it can call
- The data it can see
- The checks on its output
- The evidence that it is doing the job
What we deliver.
What an engagement can include. Scope is agreed in writing before work starts.
- Workflow selection and feasibility check
- Agent and tool architecture
- Retrieval over your documents and data
- Model and API integration
- Evaluation harness and regression cases
- Guardrails and human review paths
- Observability, cost, and latency controls
- Agents embedded in existing products
Ways to engage.
Four shapes the work can take. Most engagements start small and grow into ownership.
Agent build
Design and ship the agent, its tools, and the systems that keep it honest.
Product integration
Put an agent inside a product that already exists without breaking what works.
Reliability partnership
Improve evaluations, monitoring, cost, and latency over time.
How it runs.
Recorded like a drawing's revisions: what changed, and who signed it.
- A
Frame
Define the user, the decision, the context available, and what success looks like.
- B
Evaluate
Build the test cases and failure categories before scaling the implementation.
- C
Ship
Integrate the model, tools, data, review paths, and operational controls.
- D
Learn
Watch real behaviour in production and improve the system with evidence.
Questions
Before we start.
Practical answers about this kind of engagement.
No. We first test whether an agent creates enough value to justify its cost, its uncertainty, and its operational burden. Ordinary software is often the better answer, and we will say so.
Start a project
Let's build the thing that changes your business.
We reply within [PLACEHOLDER: reply time]. You get a written first step, whether or not you hire us.
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