Fintech software development, built to pass review.
Payment platforms, compliance checks that run before money moves, and migrations under live payment traffic. One platform processed $41.2M in its first year. Agents around it start at $8,000, flat.
4.6 from 18 Google reviews2 fintech builds published, with what each client paid
| Lien waiver | Signed, right amount and period | Pass |
|---|---|---|
| Insurance certificate | Meets the contract minimums | Pass |
| Draw terms | Retainage does not match the schedule | Blocked |
| Release | Waits until every rule passes | Held |
- $41.2Mprocessed in the payment platform's first yearCase study
- 0.02%processing error rateCase study
- 67 days → 12 daysdays for subcontractors to get paidCase study
- Zerodowntime moving $14M a month from Heroku to AWSCase study
One compliance gap can shut you down. One payment failure can end a customer.
Money waits on paperwork, reviewers ask for evidence nobody kept, and the platform has to change while payments keep flowing. We build the system that holds up to the review.
of compliance documents verified automatically in the payments platform we built. The rest went to a person, with the reason attached. Read the case study
Today
- Payments wait while someone checks documents by hand.
- A blocked payment comes with no reason the customer can act on.
- The security review asks for an audit trail that was never kept.
- Infrastructure changes are risky because payments never stop.
With Gigabit
- Rules check every document and term before money moves.
- Each check returns pass or fail with the exact reason.
- Every action, by a person or an agent, is logged.
- Services move one at a time, with shadow traffic and a tested rollback.
What we build for fintech teams.
Three of these are shipped and running, with published numbers. The fourth uses the same method and says so.
Payment platforms with ledgers that match to the cent.
Multi-method payments with custom splits on Stripe Connect, a double-entry ledger and a portal for each side. One platform cost $118,000 over 4 months and processed $41.2M in its first year at a 0.02% error rate.
| Draw approved | Split between contractor and subs | Scheduled |
|---|---|---|
| Ledger entry | Debits equal credits | Balanced |
| Subcontractor payout | Released after compliance passed | Paid |
Checks that hold the money until every rule passes.
A rules engine blocks a payment until every document and term verifies, and returns the exact reason when one does not. 94.6% of compliance documents verified automatically; the rest went to a person.
| Lien waiver | Signed, right amount | Pass |
|---|---|---|
| Prior settlement | Previous payment settled | Pass |
| Retainage release | Not yet a verified event | Blocked |
Infrastructure moves under live payment traffic.
A payments platform handling $14M a month moved from Heroku to AWS service by service, with shadow traffic and a tested rollback at every step. Downtime: zero. Deployment time fell from 38 minutes to 2.5.
| Ledger service | Shadow traffic, no discrepancy | Moved |
|---|---|---|
| Payment core | Traffic moving from 1% to 100% | Shifting |
| Rollback | Tested at every step | Ready |
Agents on the exception queue, with a person on the decision.
Onboarding document handling, transaction-monitoring triage, reconciliation and support copilots. The agent extracts, classifies and drafts the reason; a person decides anything that moves money.
No published case study for this one yet. Same method, stated plainly.
AI for KYC and KYB| Onboarding document | Fields extracted, one mismatch | Needs reviewer |
|---|---|---|
| Flagged transaction | Pre-sorted by risk and value | Queued |
| Bank match | Matched to the invoice | Reconciled |
What your providers already do, and what we add.
Identity, fraud and payments are bought from specialists. We build the workflow, the ledger and the evidence around them.
- Identity verification: document and liveness checks.
- Payment processing, with the provider's own fraud scoring and disputes tools.
- Bank data and account connections.
- Documents collected, structured and checked against your written rules.
- Exception queues where an agent prepares the case and a person decides.
- Ledgers, payout splits and reconciliation that match to the cent.
- An audit trail on every action, ready for the vendor security review.
Built for the security review.
We design to the standards your auditors and partners require, and state what is actually in place.
PCI-DSS-aware architecture.
Payment and cardholder-data flows designed to the standard your review expects, not bolted on at the end.
SOC 2 path and GLBA awareness.
We build toward the controls your auditors and partners require, and document what is in place.
Audit trails on every agent action.
Every step is logged, so you can answer the questions a vendor security review asks.
Rules where a decision must be explained.
Checks that release money are explicit rules with a reason, not a model's judgment.
A person on money movement.
Agents prepare; a person approves anything that moves funds.
Tested before launch.
The payments platform passed a third-party penetration test after two medium findings were fixed.
We claim no certification we don't hold. An AI security assessment red-teams an agent before it touches financial data.
Two fintech builds, with the numbers.
What each client paid, how long it took, and what happened afterwards.
A construction payments platform built in 4 months for $118K processed $41.2M in year one with a 0.02% error rate.
A 14-week strangler-fig migration off Heroku with zero downtime: −35% infra cost, −93% deploy time, +800% deploy frequency.
For build price, monthly cost and payback across every project we publish, see what client projects cost.
Fixed prices, on the page.
Every engagement has a price in writing before work starts. You own the code and the evidence trail.
AI Transformation Sprint
You know a queue holds money back, not which one to fix first.
- Every check that can block a payment, listed with the dollars waiting
- ROI model and build-vs-buy
- Ends in a deployed pilot
- Credits toward an agent build
Gigabit Agents
One exception queue or workflow is clear.
- The finished agent, built and deployed in your stack
- A person on every money decision
- Evaluation set and audit log included
- You own the code
AI Security Assessment
An AI feature has to pass a partner's or auditor's security review.
- Threat model of the agent or LLM feature
- Red-teaming for prompt injection and data leakage
- Graded report
- Remediation plan
Rules release the payment. Agents clear the paperwork.
In construction payments a general contractor cannot release funds until the compliance pack clears. These are the checks the platform we built runs before any payment moves.
| Check | What must be true before release | What goes wrong if it is skipped |
|---|---|---|
| Lien waiver | Signed, for the right amount and the right period | Lien risk on the project |
| Insurance certificate | Current, and meets the contract minimums | A coverage gap the general contractor owns |
| Contract and draw terms | The draw matches the schedule; retainage is right | Overpaying, or withholding too little |
| Prior settlement | The previous payment actually settled | A double payment or an orphaned draw |
| Retainage release | Released as its own verified payment event | Withheld funds released early |
Retainage is typically 5–10% withheld per payment, tracked per subcontractor per project. 94.6% of documents cleared automatically. The 5.4% that did not is where an agent earns its keep: extract the fields, classify the document, draft the reason and route it to a person. Rank your own queue the same way: list every check that can block a payment, put the dollars waiting next to each, and start with the largest one that has a written rule.
How it runs, and what you receive.
- 01
Scope
One call, then a written plan: the workflow, the data it touches, what a first release covers and a fixed price.
- 02
Build
Short sprints with a demo on staging. Every AI release passes an evaluation set built from your real cases.
- 03
Launch
Live with a person on the risky steps and an audit log of every action.
- 04
Run
We monitor, re-run the evaluations and fix, or hand over to your team with docs and runbooks.
- The code, in your repositories
- The evaluation set and its latest report
- Architecture notes and a runbook
- An audit log of every agent action
When we fit, and when we don’t.
Choose us when
- You run a payments, lending or finance-operations product.
- Money or onboarding waits on documents and manual checks.
- A partner, bank or auditor will review what you ship.
Look elsewhere when
- You need identity verification itself. Buy it from a specialist provider; we integrate it.
- You want a model to decide what money moves. We use rules there, with a person on exceptions.
- You want a demo for a pitch with no review behind it. Prototype tools compared
We are not a demo shop pointing a model at financial data and hoping it passes review. Where a decision has to be explained and repeated exactly, we use rules, not a model.
Go further.
Fintech app development
Payment platforms, ledgers, portals and compliance checks.
Open FintechAI for KYC and KYB
Which onboarding steps an agent can prepare, and where a person decides.
Open PlatformNetSuite integration
Orders, refunds and payments kept in agreement with the books.
Open ServiceAI security assessment
A graded report your security reviewer can read.
OpenQuestions fintech teams ask.
Something else? Book a call with an engineer.
How much does it cost to build a payments platform?
One Gigabit client, a seed-funded B2B construction payments startup, paid $118,000 for an MVP built in 4 months: Stripe Connect payments with custom splits, a compliance engine, contractor and subcontractor portals, and a full audit trail. Ongoing development and support continued at $8,500 a month. It processed $41.2M in its first year. That is one engagement, not a price list.
Can you migrate a payments system without downtime?
We have done it. A Series B payments platform processing about $14M a month moved from a Heroku monolith to AWS in 14 weeks for $74,000, with zero downtime. Services were extracted one at a time, the payment core last, after 48 hours of shadow traffic across 12,000 transactions showed no discrepancy, and traffic shifted from 1% to 100% over 10 days.
Do you build KYC and identity verification?
We have not published a KYC case study, so we do not claim one. Identity verification is usually bought from a specialist provider and integrated. What we build is the workflow around it: collecting and structuring documents, checking them against rules, routing exceptions to a reviewer and logging every decision. Our published fintech work is payment-compliance verification, where 94.6% of documents were verified automatically.
Is the compliance engine AI?
No, and deliberately. In the payments platform we built, the checks that release money are explicit rules: each returns pass or fail with a specific reason, so a contractor sees exactly what is blocking a payment. Rules are the right tool when a decision must be explained and repeated exactly. Agents fit around them, on triage, document handling and support.
Where do AI agents pay off first in fintech payments?
On the documents that hold money back, not on a customer chatbot. In the construction payments platform we built, a rules engine checks the lien waiver, insurance certificate, contract and draw terms, prior settlement and retainage before any payment releases. 94.6% of compliance documents cleared automatically; the other 5.4% went to a person. That exception queue is where an agent belongs: extracting fields, classifying the document and drafting the reason for review. The release itself stays with the rules.
Is Gigabit's fintech work compliant?
We build PCI-aware, SOC-2-path architectures with audit trails and sign the agreements your security review requires. The payments platform launched with audit logging, role-based access, encrypted storage and documented change management, and passed a third-party penetration test after two medium findings were fixed. We state what is in place and do not over-claim.
What fintech workflows do you build?
Shipped and running: payment platforms, compliance checks that gate payment release, and zero-downtime infrastructure migrations. We also take on onboarding document handling, transaction-monitoring triage, reconciliation and support copilots with audit trails, though we have no published fintech case study for those yet.
From the field notes
Build the system that passes the audit.
Bring the workflow: payments, compliance checks, monitoring, reconciliation or support. A senior engineer replies with a scoped plan and a fixed price.
- The workflow and the money it holds
- The rules that must be explained
- What the security review will ask
- A fixed price, in writing