What does Buildify do?

Buildify is a founder-led applied AI studio. We design, build, and ship production AI systems for organizations with complex or regulated workflows, end to end, from architecture to the running system.

What kind of work does Buildify take on?

Document and extraction pipelines, validation and compliance review, decision support and matching engines, and AI integrated inside platforms like Salesforce. The common thread is work where wrong answers have real consequences.

How is a production AI system different from a demo?

A demo calls a model and shows a happy path. Production is everything around it: the pipeline, the guardrails, the human-in-the-loop handoff, and the system it lives inside. The model is about 10 percent of the work; Buildify builds the other 90 percent.

How does Buildify handle the risk of wrong AI answers?

Systems are designed to flag what they are unsure about and route those cases to a human, rather than hand over a confident wrong answer. Recommendations show their reasoning so a person can verify them.

How many systems has Buildify shipped?

Six production AI systems are live in regulated environments, spanning government procurement, compliance review, case management, and child-welfare decision support.

Who builds the work at Buildify?

Buildify is founder-led. Kalpesh Mahida builds the systems end to end: architecture, prompts, infrastructure, interface, and deploy, solo or embedded with a small team.

← All systemsCivic Services

311 Voice Deflection

A multilingual voice front-end on a 311 line, built entirely on AWS and sitting over the same Salesforce routing engine that powers the on-screen console. One brain, two front-ends.

Amazon ConnectAmazon LexNova SonicSalesforceLambda

All-AWSVoice over a Salesforce brain

MultilingualEnglish, Spanish, Chinese

Deflect or transferRoutine vs live agent

The problem

A 311 line takes the same routine requests over and over, mixed with the occasional urgent or unclear call that genuinely needs a person.

Every one of those calls tied up a live agent, whether it needed one or not.

How it works

Extract, verify, then route the unsure to a human.

route_to_human.pipeline Confident · auto Unsure · to a human

Incomingcases · docs

Modelconfidence

Human review

Flagged cases

Auto-resolved

Confident, cited

Listen in any language

The caller speaks naturally; the voice layer transcribes and understands the request across multiple languages, then hands it to the routing engine.

Route on one brain

The same Salesforce engine behind the staff console decides the outcome, so voice and screen always agree.

Deflect or transfer

Routine requests become a case and are resolved on the call; unclear or urgent ones are handed straight to a live agent.

What shipped

Routine requests are handled end to end on the call, so agents get the ones that actually need a human.

Voice and the staff console share a single engine, so the logic never drifts between the two.

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