AI Automation · Build with PTAS AI
AI Product Development
A product built around your workflow, on the platform DocPro and FinSuite already run on, so the agents, the audit trail and the integrations exist before the first sprint.
What it is
A thin product on a thick platform
The product is the part your users see. Most of what makes it work, the agents, the confidence scoring, the review queues, the audit trail and the integrations, already exists underneath.
AI product development here means building a product, internal or customer-facing, whose core job is to understand documents and data, make or recommend decisions under rules, and act inside business systems. A supplier portal that reads and validates invoices on upload. A lending back office that reads bank statements and builds the file. An operations app that turns delivery paperwork into stock movements. The product is new. The engine underneath it is the one DocPro and FinSuite run on.
Four of our capabilities sit close together, so it is worth saying which this is. AI Agent Development builds or tunes individual agents. Enterprise AI Development puts AI inside the systems you already run, which the Enterprise Automation page covers. Application Modernization rebuilds something you have. AI product development is when the output is a product in its own right, with its own users, roadmap and release cycle.
The honest limit is that we build on our own platform. If a product needs a model trained from scratch on a data type nothing reads yet, or has no document, decision or system component, we say so in discovery rather than after a contract. Where it fits, the first release is measured in weeks rather than quarters, and we quote a typical range rather than a date.
What we build
Six kinds of product this fits
The common thread is paperwork or data coming in, a decision in the middle and a business system at the end.
Customer-facing
Supplier and customer portals
Invoices, claims or applications uploaded, read and validated on the spot, with the user told what is missing before anyone internal sees it.
Customer-facing
Vertical SaaS with document AI
A product for accountants, lenders, logistics firms or insurers whose core feature is reading the paperwork their clients send.
Internal
Finance operations platforms
The AP, reconciliation and compliance queues of a group in one product, shaped to its entities and approval structure.
Internal
Operations and back-office tools
Delivery notes, gate passes, inspection reports and work orders turned into transactions, with the exceptions routed to a person.
Agent-assisted
Service and case management
Cases read, enriched from your systems and triaged by agents, with people handling the ones that need judgement.
Data products
Reporting and data products
Structured data extracted from documents at scale, validated, and delivered as a dataset or an API your other products use.
How PTAS AI builds it
Discover, design, build, run
The same four moves every PTAS AI capability runs, applied to shipping a product. Discovery ends with a scope, a boundary and a number, whether or not a build follows.
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01
Discover
Two to three weeks with the people who do the work: the documents, the decisions, the systems and the exceptions. We define what the product decides on its own, what it recommends and what it leaves to a person, and agree what good looks like in numbers.
A scope, a boundary and a measure, before any build
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02
Design
The product is designed as a thin layer on the platform: which agents, which rules, which review queues, which integrations. Screens are designed around the exception, because the routine case should not need a screen at all.
Thin product, thick platform
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03
Build
Short releases, each run against real documents and real cases rather than fixtures. The platform supplies confidence scoring, review, audit and integration; the team builds what is specific to your product, and only that.
Weeks to a first release, not quarters
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04
Run
Launch with one team or one workflow, measure against the numbers agreed in discovery, and improve from the record of what the agents saw and decided. Ownership, hosting and support are agreed up front, and the roadmap is yours.
Improved from the record, not from guesses
The path
What the first sixteen weeks look like
Each step hands the next one something concrete: a scope, a boundary, a prototype on real documents, a release in use. Nothing waits for a big reveal.
From idea to a product in use
- 01 Discover The workflow, the users and the documents
- 02 Define What the product decides, and what it does not
- 03 Prototype Real documents through real agents, early
- 04 Build The thin product on a thick platform
- 05 Integrate The systems on either side
- 06 Launch One team, one workflow, measured
- 07 Run Improved from the record, not from guesses
Discovery ends with a scope and a number. The prototype runs on your documents before the build starts, and the first release goes to one team, measured against what discovery agreed.
Real documents from week two
Prototypes run on your paperwork, so the hard cases surface early.
Governance is inherited
Confidence scores, review queues and the audit trail come with the platform.
Measured against discovery
The product is judged on the numbers agreed before it was built.
What you get
What comes with the product
Four things that are usually negotiated at the end of a build, settled at the start of this one.
A product that is yours
The product code, your data and the roadmap are yours; the platform underneath is licensed. Who owns what is written down before the build starts, not negotiated after.
Security by design
Role-based access, masked identity fields, retention under your policy, and cloud, private cloud or on-premise deployment where supported, with ISO/IEC 27001-aligned practices.
An audit trail from day one
Every decision the product makes carries what the agent saw, which rule applied and who reviewed it. Your auditors and your customers can both ask why.
A team that stays
The engineers who built it run it with you after launch, on terms agreed up front, until your own team can, or for as long as you prefer.
Product connection
What the product is built on
Every product we ship runs on the Agentic AI Platform and draws on DocPro and FinSuite where it touches documents or finance. What is built new is the product around them.
FAQ
Questions founders and product owners ask
How is this different from hiring a software development agency?
An agency starts from an empty repository. We start from a platform that already reads documents, scores confidence, runs review queues, keeps the audit trail and posts to ERPs, so what gets built is the product around those. The team has shipped its own products, DocPro and FinSuite, on the same platform, which is a different kind of evidence from a portfolio. The trade is that your product runs on our platform, and we are clear about what that means for ownership and hosting before you commit.
Who owns the product?
The product code, your data and the roadmap are yours. The platform underneath is licensed, like any runtime a product depends on. This is written into the engagement before the build starts, including what happens if you later take the product in-house.
What if our idea needs something the platform does not do?
We say so in discovery. A new document type is a custom agent and a normal part of the work. A capability with no document, decision or system component is not, and we would rather point you elsewhere than build something we would not run ourselves.
How long to a first release?
The typical range is eight to sixteen weeks to a first release in use by one team or one workflow. It is indicative and varies with document variety, integrations, deployment and how settled the decisions are. Discovery is two to three weeks of that and produces a scope and a number either way.
Can you also run it?
Yes. Hosting, support and the improvement cycle are part of the engagement if you want them, on terms agreed up front. Many teams start that way and take over once the record shows how the product behaves.
Keep reading
Related capabilities
Build with PTAS AI
The full set of engineering services, from a focused pilot to a programme.
Read more →AI Agents
The agents an AI product is assembled from.
Read more →Agentic AI Platform
The runtime underneath every product we build.
Read more →Custom Enterprise Automation
When the output is a workflow rather than a product.
Read more →Next step
Bring the product idea and the paperwork behind it
Discovery takes two to three weeks and ends with a scope, a boundary and a number, whether or not you build with us.