How DrakoAI Works

We turn fragmented NYC construction data into role-specific signals you can act on.

Public data → unified context → role-specific decisions

View as:

From filings to real-world job context

NYC DOB

Permits, filings, construction activity

ACRIS

Ownership changes, transfers, financing

PLUTO

Building type, zoning, size, constraints

NYC Open Data

Complaints, enforcement, violations

Permits show intent. Ownership, building history, and complaints reveal execution risk.

Where permits turn into a job worth pursuing

Normalize

Clean inconsistent filings so timelines and scope can be compared.

Entity Resolution

Link permits, buildings, owners, and contractors into one job view.

Historical Aggregation

See how similar jobs progressed — delays, restarts, and outcomes.

This is where filings become actionable pursuit.

Signals that tell you which jobs are real, risky, or worth walking away from.

Early-stage job activity

Pursue before competition intensifies

Permit velocity changes

Adjust pursuit intensity and timing

Ownership turnover

Flag risk or avoid unstable owners

Complaint spikes

Avoid jobs with execution friction

Contractor patterns

Target reliable clients, avoid problem GCs

Signals reveal which jobs are real, risky, or worth avoiding.