AI for GovTech software companies

Your government software, with AI that shows its source and leaves every decision to agency staff.

For tax, fines and payments, records and public safety software with agencies already on it. We build AI into your product, keep agency data in your cloud or on their own servers, and ship it under your name.

  • Every answer and match shows its source
  • Agency staff approve every change to a record
  • Runs in your cloud or the agency's own data center

Three ways to start, from $5,000: Build Sprint · Planning Sprint · AI Scorecard

app.civara.example / harlow-county / tax / batches

Harlow County Tax Office · Today's batches

AI checked
BatchDifferenceStatus
Counter · cash and check$0.00Balanced
Lockbox file · bank$1,284.10Cause found
Online portal · card$0.00Balanced

Civara Assistant

2 lockbox items posted to the wrong notice

  • Every match shows the file line
  • Nothing moves until the balancer approves

Correction waiting for the balancer

Lockbox lines 41 and 42 carry parcel 07-118-3 but posted to 07-181-3. Move both to the right notice, then the batch balances.

Open the two itemsApprove the move

Balancely by Datics AI · Try it step by step →

Illustrative demo on a fictional county. Not client work.

Why AI stalls in government software

What gets in the way, and how we handle it.

  1. 01

    Public money that must balance

    Explain, never post

    AI finds and explains each difference; the balancer approves every correction before it posts.

  2. 02

    Answers nobody can trace

    Cite, or decline

    Every answer cites the record and page it came from, and says so when the records are silent.

  3. 03

    Data that cannot leave

    Your cloud or theirs

    Self-hosted models in your cloud account or as a release in the agency's own data center.

  4. 04

    Agencies that must never mix

    Scoped per agency

    Every lookup filtered by agency, role and clearance first, and closed when a check fails.

  5. 05

    AI that could change a record

    Staff decide

    AI reads, matches and drafts; agency staff approve each change, and every step is logged.

Why AI earns its place in your product

Close faster

Month close without the hunt.

Balancers see why a batch is off and approve the fix, instead of searching files line by line.

Fewer calls

The public answered from the record.

Taxpayers and defendants get what they owe and why, with anything else sent to staff.

Easier to buy

Built for public scrutiny.

Sources shown, staff deciding and data kept where the agency needs it make your answers to procurement short.

Modules by Datics AI

Start from work we have already delivered, not from zero.

AI for government software you can see before you buy: each module runs on a fictional county and builds on tax, payments, records and public safety work we have delivered. The list also includes one service.

  • When a batch does not balance, balancers see which payments caused it and approve the fix.

    Fits: Property tax collection, fines and fees, court payment and treasury software

  • Taxpayers and defendants ask what they owe and why, and get the answer from their own notice or citation.

    Fits: Property tax portals, fines and fees and court payment portals

  • Clerks and archive staff ask the records a question and get an answer cited to the page, or a clear decline.

    Fits: Records management, archive, minutes and agenda, and document management software for agencies

  • Votes, bills, filings and donations from scattered public sources linked to the same person, with the source on every number.

    Fits: Civic, transparency, open data and public records products

  • Supervisors see which alerts led to an incident, with the reasons, and confirm each link up the approval chain.

    Fits: Situational awareness, incident management and public safety software

  • Tax, payments and records platforms modernized and extended while every agency keeps working.

    Fits: Tax, fines and payments, records and public safety platforms with live agencies

Also for your product

Your product, inside Claude and ChatGPT.

We build a connector so your users can ask their own AI assistant about their data in your product, each signed in with their own login and seeing only what they can already see. It starts read-only, only the fields you approve leave your product, and actions each user approves can come later.

How we build connectors
Illustrative example · A tax office balancer, in Claude

Which of today's batches have not balanced yet?

One: the lockbox batch, off by two payments. Here are the file lines behind them.

Proof

Our government software work.

Property tax and fines and fees platforms for a government payments software company, cited records AI for Neno Technologies (NenoBrief and NenoDoc Lexicon), CivicQ's public data platform, and a situational awareness system for a large public security organization.

57 featured AI case studies across our work

Government payments software company

Tax collection · Every channel on one notice

Tax offices collect from every channel and balance each month to the cent

Offices ran tax season on an old desktop system. Now one web back office takes every channel, disburses each dollar and closes the month.

ModernizationMulti-tenantIntegrations
Read case study

NenoBrief by Neno Technologies

Records AI · Cited answers in production

Archive officers get cited answers inside their live document system, files never copied

Archive records could not reach an outside AI. Now the client's live document system calls our self-hosted gateway for cited answers.

Brownfield AIInside a live productCited answers
Read case study

Large public security organization

Public safety · Alerts to outcomes

Security leaders trace each alert to its outcome, seeing only approved records

Alert, incident and response records sat apart across many teams. Now they are linked on one map and appear only after approval.

Data foundationPermission-awareHuman approval
Read case study

More government software work

Government payments software company

Fines and fees · Payment portals

Sheriffs and courts take fines online and at the counter on one portal

Fines were paid at the counter in cash or check. Now each agency has its own branded portal for card, bank and front desk swiper payments.

ModernizationMulti-tenantInside a live product
Read case study

CivicQ

Public data · Every number sourced

Voters see how their representatives vote, trade and fundraise, each number sourced

The record was public but spread across many government sites. Now one profile links votes, bills, trades and campaign money, sources shown.

Data foundationIntegrationsCited answers
Read case study

Large public security organization

Public safety · On-premise releases

A geospatial system that runs in the client's data center, without vendor access

The data is too sensitive for us to host or reach, so each release ships as a tested VM and the client's own admins run the rest.

Data foundationRuns in client cloudPermission-aware
Read case study
See all our AI case studies

How it works

Three ways to start, each at a fixed price.

A 30-minute review tells you which one fits. Whichever you pick, you know the production price before you commit, and your fee counts toward it.

GovTech Platform Product Review · 30 minutes, no chargeStart here. We look at your platform with you, agree the outcome you want for your agencies, and tell you which of the three below fits.

Book a 30-minute Product Review

No AI yet, and a module fits

Build Sprint

$10,000 fixed3 weeks

Pick it when: One of our modules delivers the outcome you want.

Balancely · Payly · Indexly · Sourcely · Alertly

  • One agency outcome (2 to 3 related capabilities) working in your staging, behind a feature flag
  • Pull requests to your repo, built on a fictional county's sample data
  • Quality and safety evals, the cost per agency and a packaging recommendation
  • A fixed-price quote for production

Something new, or a plan first

Planning Sprint

$5,000 fixed2 weeks

Pick it when: You need something our modules do not cover, or want a plan before you build.

  • Where AI fits across your platform, including beyond our modules
  • A prioritized capability map, with what each one depends on
  • A readiness review of your architecture, data, integrations and permissions
  • A fixed-price quote to build it and take it to production

AI already built or tried

AI Scorecard

$5,000 fixed2 weeks

Pick it when: You have already built or tried an AI feature in your platform, live or not.

  • One AI feature you have built, tested in staging on 50 of your own cases, with names and contact details removed
  • Tests for invented answers, another agency's records, changed amounts and prompt injection
  • Cost per agency and a packaging recommendation
  • A scorecard, ranked fixes, draft security answers and a fixed quote

Not a compliance audit or certification.

How the AI Scorecard works

Production, at a fixed quote

We take what your Sprint built or planned live for your agencies, by pull request, with no standing production access. It typically includes load testing at your busiest season and a spend cap per agency. Your Sprint or Scorecard fee counts toward it.

After go-live, optional support

The product is finished and yours to run. If you want us to stay on: a named lead engineer, a monthly quality and cost report, testing before any model change, and more capabilities, each at its own fixed quote.

Stop after any Sprint and keep what you got.

How a Build Sprint runs

  • In the setup week we map your platform, agencies and roles and agree what the Sprint touches.
  • We follow your coding standards, tests and CI; your engineers review and merge every pull request.
  • Half at signature, half when the Sprint Pack is delivered.
  • Your time: about 2 to 3 hours a week from a product owner, plus an engineer to review pull requests.

Need integrations first? GovTech platform engineering covers live platforms changed without stopping. Ask in the Product Review.

Built for public records and public money

Controls your customers' security reviews ask about.

Each control is a design fact about how the module is built and how we work, not a compliance claim.

  • Staff decide

    Corrections, links, replies and published data change only when agency staff approve them.

  • Every answer sourced

    Answers cite their record and page; matches show the file line or field behind them.

  • Scoped per agency

    Every lookup filtered by agency, role and clearance first, and closed when a check fails.

We work within your CJIS, PCI DSS, public records, accessibility and privacy requirements and your agencies' contracts. Compliance depends on the complete product, contracts, policies and operating environment; Datics does not present software engineering alone as certification or government authorization.

How we handle public records and agency data

In AI and data since2018

  • AWS: Select Tier Partner
  • Anthropic: Partner · Claude models
  • CopilotKit: Agent user interface
  • LangGraph: Production agent engineering
  • Databricks: Governed AI & agent workflows
  • Cursor: Agentic development environment
  • Microsoft Azure: Production AI delivery
  • Google Cloud: Production AI delivery

AI shipped inside products for

Peerlogic logoAMove logoDealership Toolkit logoIdeeza logoRVP Pricing Tool logo

Questions we hear on the first call

Straight answers before you book.

The questions GovTech product and engineering leaders ask most.

Do you build AI for local government?

We build for the software companies that serve local government: tax offices, sheriffs, courts, clerks and archives. If your product brings AI into an agency's daily work, we build it inside your product, under your name, for your agencies.

Do you sell to agencies or answer public bids?

No. We work for the software company, in its repository and under its name. The agency contract, procurement and support stay with you.

Can the AI change an amount, a record or a published number?

No. It reads, matches, explains and drafts. Agency staff approve every correction, link and reply, and every step is logged with who approved it.

Can it run without sending agency data to an outside AI service?

Yes. We have built records AI that runs fully self-hosted on client-owned GPU hosts, and delivered a system as tested, versioned releases into a large public security organization's own data center, where we had no access.

How do you keep many agencies apart on one platform?

Each agency keeps its own settings, rules and data. Every lookup is filtered by agency, role and clearance before anything else runs, and we test that one agency's records never reach another's.

Do you need agency data in the Sprint?

No. Sprints run on a fictional county's sample notices, payments, records and alerts in your staging, and code reaches your product as pull requests.

How do you choose a government software development company?

Look for a team that has changed live government platforms without stopping them: money that balances to the cent, records that stay where the agency needs them, and roles that keep offices apart. Ask how the team handles month close, who decides when the AI is wrong, and who owns the code. We answer each of these in the Product Review, with the work behind it.

Who owns the code?

What we build for your product lives in your repository and ships under your name. The reusable engine underneath stays ours and is licensed to you; the terms are in your contract.

Do you have SOC 2 or FedRAMP?

Not yet, and we hold no government authorization of our own. We work in your staging by pull request, under your accounts, and in production only through access you grant and can revoke.

Where are you based?

Datics is headquartered in Austin, Texas, with a named lead engineer and US-hours overlap on every engagement.

GovTech insights

How we think about the hard parts.

Answers for product and engineering leaders, from the team that builds it.

AI security and compliance

How does RAG security scope retrieval to user permissions?

RAG security in multi-tenant SaaS starts with whose documents a question may search. Learn how to filter by tenant and permission before ranking.

Rana Umar Majeed · Oct 20, 2026

AI security and compliance

How do you build an AI audit trail you can reproduce?

An AI audit trail records who or what made each change, with which inputs and model, so reviewers can tell AI entries apart and reproduce any output.

Rana Umar Majeed · Sep 4, 2026

AI security and compliance

How do you enforce tenant isolation beyond database rows?

Tenant isolation beyond database rows means boundaries per field and per role, in caches, files, payments and jobs, so no tenant sees what another owns.

Rana Umar Majeed · Oct 29, 2026

AI agents

Where should human in the loop AI review happen?

Human in the loop AI works when review happens field by field, before anything ships. Learn where to place checkpoints and how to measure accuracy.

Rana Umar Majeed · Oct 16, 2026

AI security and compliance

Soft delete vs hard delete: which fits regulated software?

Soft delete vs hard delete in regulated software: when to suppress, when to purge, and how to keep the audit history that disputes depend on.

Rana Umar Majeed · Oct 26, 2026

Brownfield AI

How do you build an AI data pipeline from outside sources?

An AI data pipeline for outside sources needs a reviewed data model and ETL that links records to real entities. Learn how to plan sources and mappings.

Rana Umar Majeed · Sep 9, 2026

See it on your own platform.

Bring one product, workflow or AI feature. In 30 minutes we tell you which of the three ways to start fits, what it would cost to serve per agency and what agencies will ask about it.

Own several government software products? Datics for private equity 

Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.