Giggit AI helps small and mid-size businesses put AI agents to work where mistakes are costly. We design, build, and test systems tuned on three dials: speed, quality, and cost. They log every step, score every decision, and stay within the limits you set. A person signs off on the critical steps.
What should the agent own?
Deciding what an agent does on its own, and what it hands to a person, sets everything downstream. We scope those boundaries, design the tools and orchestration, and build the simplest loop that holds up on real inputs. One agent proposes and others check.
What you get: a working agent workflow plus a record of every autonomy decision, so the next engineer never has to guess the intent
Can it show its sources?
Retrieval pipelines measured end to end, from ingestion to reranking. Knowledge-graph layers (GraphRAG, entity resolution, org and risk graphs) where relationships carry the answer. Every answer traces to a source.
What you get: retrieval quality you can measure, and answers that cite where they came from
How do you know it works, and what happens when it fails?
Most agent prototypes are anecdotes. We build the measurement layer first: calibrated scoring, trajectory-level evaluation that grades how the agent reached an answer, and regression suites on every change. Then the brakes: budget ceilings, step caps, circuit breakers, escalation paths. Failure drills show them firing before you rely on them.
What you get: an evaluation harness in your repo, baseline scores, runtime controls with drill results, and documentation for model-risk review
What can a small team actually run?
A five-person company needs three workflows that stop eating the founder's week, and a platform is rarely the answer. We advise on AI strategy, model and vendor selection, and workflow redesign, sized to your headcount. That includes the AI bill: the expensive model runs only on steps that need it, routine steps run on cheaper ones, and the measurements decide which is which.
What you get: a decision you can defend with the trade-offs on paper, a runbook a non-engineer can follow, and clear advice when the answer is a simple scheduled script
Engagements run in short loops with a checkpoint at every step. Scope is fixed, and the success measure is agreed in writing before work starts. If the pilot's numbers do not clear the bar, you get a short, clear answer instead of a long, expensive one.
A few engagements run at a time. When the calendar is full, we say so.
A short call is usually enough to tell whether we are a fit. You leave with a clear read on what agents can and cannot do for you.
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