Permitting Delays Aren't a Bureaucracy Problem. They're an Information Problem.

The common complaint about building permits is that local governments move too slowly. Developers blame red tape. Homeowners blame indifferent city staff. But a growing number of state legislatures have concluded the deeper issue isn’t attitude; it’s information: the data planners need to answer a simple zoning question – what can I build here? – usually exists somewhere, but it’s scattered across GIS databases, ordinances that can run hundreds of pages, and institutional knowledge that lives only in colleagues’ heads.

That diagnosis is now showing up in law, not just industry commentary. California’s AB 1308 imposes a 10-business-day “shot clock” on certain residential building inspections. Florida’s HB 267 and SB 180 set fixed statutory deadlines for permit approvals with automatic fee reductions for missed ones. Georgia’s SB 447, signed in 2026, sets firm review windows – as short as 45 days for an initial review – with automatic approval as the penalty for missing them. Texas has adopted similar deadlines, and several other states, including Wyoming, Kansas, Oregon, and Nebraska, have passed comparable “shot clock” reforms. The mechanism varies by state, but the logic is the same: force planning departments to act within a predictable window rather than letting review timelines drift.

Shital Dhakal, founder of Conflation Labs, spent years working inside municipal planning departments in the San Francisco Bay Area before building a zoning and permitting data platform aimed at the resulting bottleneck. His diagnosis of the underlying mechanics is specific. “The ordinances are so convoluted, so long, and for a layperson, it’s just hard to consume all of that information,” he says. Planners answering a single zoning question must pull from GIS databases, local ordinances, development standards, and institutional knowledge — a process that gets no faster just because a new law demands a faster answer.

Why a Simple Question Takes All Day

When someone calls a planning department to ask whether they can build a two-story commercial building on a given parcel, the staffer has to pull up GIS records, locate the correct zoning district, cross-reference it against an ordinance that can run to a thousand pages, check development standards like setback and parking requirements, and synthesize an answer. A follow-up question restarts the cycle.

A handful of platforms have emerged to compress that process. Zoneomics, one of the more established players in this space, has built a nationwide zoning-data platform used by firms including Cushman & Wakefield and Crexi, and recently launched an AI layer that lets users ask plain-language questions like “what can I build here?” and get a cited answer in seconds rather than hours. Conflation Labs, Dhakal’s platform, works on a similar premise – compressing zoning lookups into a question-and-answer format for city staff, developers, investors, and appraisers.

For commercial real estate due diligence firms, the difference this category of tool can make is practical. Dhakal says writing a zoning report typically takes an analyst about a week, since each report requires reading unfamiliar local ordinances from scratch; using a platform like his, he says, roughly half of that work can be completed in minutes. The remaining steps – obtaining zoning verification letters, final quality checks – still require a person.

Dhakal is candid about where the approach breaks down, which sets this account apart from a straightforward pitch. “One thing people get wrong about AI is they think of it in binary. Either it works, or it doesn’t,” he says. “It’s just a spectrum. You get a lot of good answers from it. But there are places where the AI cannot make a decision because the ordinance is not clear.”

State Mandates Are Tightening the Clock

The deadlines described above intend something straightforward: if an application is compliant, review shouldn’t drag on indefinitely. But cities are caught between the mandate and their capacity. Planning departments are losing staff to retirement, and Dhakal says the pipeline of younger professionals entering the planning and building workforce is thin. Budget constraints limit new hires. The staffing gap is tightening just as the regulatory clock starts running.

“Municipalities are really pressed between a hard place and a wall,” Dhakal says. “On one side, they cannot really hire as many people because of budgetary restrictions and the unavailability of human resources. But on the other side, they have to keep up with this mandate.”

Dhakal argues that data platforms like his can serve as a first-pass filter – triaging permit applications quickly so human planners spend their time on judgment calls rather than data assembly. How much that first pass catches depends on how clearly local ordinances are written, a variable that differs city by city, and government-side permitting software from vendors like Accela already plays a related role in tracking deadline compliance on the municipal side.

The Developer-City Misunderstanding

The tension between developers and planning departments is familiar to anyone in real estate. Dhakal frames it as a communication gap rooted in the same information fragmentation, not as an adversarial standoff.

“On the developer’s part, it looks like the city is knowingly making things slower, which is not the case,” he says. “They’re actually doing the due diligence, and that’s what we pay taxes for.” A planner receiving a permit application cannot simply start reviewing immediately – they have to open the drawings, understand what the plan proposes, and cross-check it against multiple regulatory layers.

Some of these platforms address that from the other direction as well: allowing architects and engineers to upload construction drawings before submitting to the city and receive automated feedback on likely code violations, targeting the common source of delay where plans are submitted only to draw correction requests weeks later, pushing the timeline back and adding cost.

The technical challenges here are real, and Dhakal doesn’t minimize them. AI struggles with edge cases in architectural plans – buildings not parallel to streets create ambiguous setback measurements, and parking lots divided into multiple sections are difficult for a system to parse correctly. “You can only solve things that you can measure,” Dhakal says, a caveat that applies as much to competing tools in this category as to his own.