Execution infrastructure for finance systems
Building theAgentic AI Platform for Enterprise Finance
NAP connects and migrates enterprise systems from a prompt. The connector builds, the ERP migrations, the exceptions and evidence and close gates in between: all of it runs as software, continuously, with every action logged.
$0.00
Variance, or the cutover does not happen
2,200+
Failure patterns encoded before your first build
SHA-256
Audit chain on every action
95%
Deterministic execution
Mission
Every enterprise runs twenty systems.
The work is in the space between them.
Nowhere is that clearer than in a migration. Moving an ERP is understood to be hard. What is less understood is that every integration pointed at the old system breaks on cutover, and most finance teams have no list of what those integrations are.
NAP turns that layer into software. It models a customer's actual finance reality, then executes across every system in the estate, with deterministic guarantees and every outcome logged in an SHA-256 audit chain.
Values
How we operate.
Four principles. They show up in the product, the partner model and the team.
01
Deterministic by default
95% of NAP's execution is deterministic code. 5% is agent reasoning at decision points. CFOs do not buy a probabilistic close. Agentic flexibility is a tool, not a foundation, and it is deployed only where reasoning genuinely beats rules.
02
Partners keep the relationship
Systems integrators, ERP companies and CFO stack software firms are not displaced by NAP. They sit closer to the customer, deliver faster, and operate with materially better economics. We do not go around the channel. We turn it into software.
03
Audit-native, not audit-friendly
Every action writes to an SHA-256 audit chain. Every decision carries evidence and policy rationale. Trial-balance variance closes at $0.00 or it does not close. The audit packet is a build artifact, not something assembled at the end.
04
Compounding memory
Every resolved exception becomes a reusable pattern and every deployment makes the next one faster. Every engagement ships carrying what every previous engagement learned. Customer number one paid for everyone after.
The team
Career consultants, building the software that replaces the work we used to sell.
Everyone here came from ERP, finance transformation, integration, and production support. We saw the same failures again and again — schema drift, intercompany variance, broken matches, and integration issues. We stopped treating them as project risks and started treating them as data.
So we’re putting ourselves out of that job, on purpose.
We encode what experienced consultants know, so every engagement starts with what the last one already learned.
Where the expertise came from
Built by people who deployed these systems, not people who read about them.
Platforms the team has built, deployed and run
And the firms they came from
BUILT TOGETHER
Our Partnership
When you deliver on NAP, it comes with the engagement: procure through existing cloud agreements, stay aligned to each platform’s roadmap, and keep model choice open.
Partner
Listed on AWS Marketplace with Private Offers, so NAP draws down against committed spend. NAP also runs in production on AWS.
Partner
Contract, CPQ and pipeline data into the CFO stack, and into revenue recognition where ASC 606 depends on it.
Partner
Finance operations workflows and approvals, connected to the same execution layer that runs the close.
Partner
Claude. Reasoning agents, and the primary model behind the reasoning agents.
Partner
Available per decision point through the same routing layer, with no change to the deterministic path.
Partner
Payment and settlement data reconciled into the ledger, with netting and classification applied before anything posts.
We're hiring
Build the system that runs enterprise finance.
Hiring engineers, ERP subject matter experts, and forward-deployed roles. We work in person.
AI / ML Engineer
Build the intelligence behind NAP.
Experience :
2–5 years
Location :
Remote / Hybrid
Frontend Engineer
Build the interfaces for enterprise AI.
Experience :
2–5 years
Location :
Remote / Hybrid
AI Solutions Engineer
Take AI from idea to production.
Experience :
2–5 years
Location :
Remote / Hybrid
Integration Engineer
Connect the systems that businesses depend on.
Experience :
2–5 years
Location :
Remote / Hybrid
Get in touch
If you run finance for an enterprise, deliver to one, or want to invest in one.
info@napsys.ai