Technical articles about digital products, AI automation, and software development.
Behind the scenes of Company OS, the decision loop that runs inside our site: why it is repo-native, how we make every decision measurable and why the AI proposes but does not decide.
Behind the scenes of the agent that discovers, qualifies and reaches out to B2B companies for us: architecture, quality gates and lessons from production.
Behind the scenes of the pipeline that classifies every inbound lead on our site: architecture, prompt injection defense, output validation and why the AI never sends anything on its own.
Honest transparency about when Chiarelli Labs isn't the right choice. Each scenario with a concrete, honest alternative.
An honest comparison between software houses, in-house dev, freelancers, RPA, and no-code. Practical criteria to decide which path fits your project.
Any dev can get GPT to extract data from an invoice in 5 minutes. The hard part is making it work every time, with any input, with visibility when it breaks.
An explanation of the contracting and project execution process at Chiarelli Labs, from first contact to delivery with a 90-day warranty.
A direct explanation of AI automation: what it is, where it actually works in B2B operations, and how to evaluate whether a process is a candidate.
Step-by-step technical guide to extracting data from bank PDFs, cross-referencing with Excel spreadsheets, and automatically generating reconciliation reports.
How to decide between building a scalable digital product or a custom internal system, with practical criteria for each situation.
How to connect legacy systems (ERP, custom systems, spreadsheets) to modern APIs without rewriting everything — with patterns, trade-offs, and when to use each approach.
Seven questions to ask before signing a contract with a software house — including what contracts usually hide and what to evaluate beyond the portfolio.