1. Days 1–20: Bottleneck Selection & Golden Dataset Construction
The biggest mistake organizations make is starting with a vague ambition like "put AI across the company." High-ROI deployments always start with one narrow, high-frequency, rules-heavy bottleneck: customs document auditing, B2B RFQ quoting, vendor invoice reconciliation, or multi-language technical onboarding.
In the first 20 days, our engineers work alongside your domain experts to collect 50 to 100 real historical cases—creating a Golden Evaluation Benchmark against which every iteration of the agent will be mathematically scored.
Executive Key Takeaways
- Days 1–20: Workflow scoping, API security mapping, and Golden Dataset creation.
- Days 21–55: Agent core build, RAG indexing, ERP/CRM sandbox integration, and guardrail testing.
- Days 56–90: Shadow-mode parallel run with human supervisors, followed by controlled production go-live.
2. Days 21–55: Sandbox Engineering & Guardrail Hardening
During phase two, we construct the agent state graph, connect read-only and sandbox APIs, and implement deterministic validation layers. Every failure mode discovered against the historical dataset is turned into an automated regression test.
3. Days 56–90: Shadow Mode & Supervised Production Launch
Before an agent is ever allowed to write to your live ERP or message a customer, it runs in Shadow Mode: processing live incoming cases in parallel with your human team so managers can compare AI recommendations against human actions with zero operational risk. Once accuracy thresholds are verified, you flip the switch to supervised production.