A model is only the beginning.
Its value depends on what happens next.
The advantage starts after the model.
Custom AI applications & workflow automation
AI systems that run inside your daily operations.
Postmodel is an AI implementation partner for healthcare and life sciences, law firms and consumer brands. We build custom AI applications and workflow automation inside the tools your team already uses, with a person approving where it matters.
Start with a defined project. Build on what works.
Before and after
A supplier invoice arrives by email.
Before. One person, 6 tools, one request.
After. Every source at once. You make the call.
The work is in the searching, copying and waiting between tools.
The system reads every source, checks what matters and prepares the result. A person approves.
Illustrative example
What we build
More capacity. Stronger operations. New applications.
Four kinds of system, each built into the tools your team already uses, with a person approving where it matters.
01 / 04
Custom AI applications
Internal tools and customer-facing applications built around a specific job, your data and the people using the system.
- A defined user and workflow
- Connections to required systems
- Improvements guided by real use
02 / 04
Operational workflows
Document collection, invoice preparation, approvals and internal requests connected into workflows with clear ownership and human review.
- Connected source records
- Documents prepared for review
- Exceptions routed to the responsible person
03 / 04
Commercial workflows
Campaign preparation, sales outreach and follow-up workflows connected to your approved content, customer data and business systems.
- Approved source material
- Coordinated follow-up
- Records of actions and outputs
04 / 04
Knowledge and information systems
Make company knowledge, procedures and technical information easier to find and use, with source references and clear handling of unanswered questions.
- Search your own material
- References alongside answers
- Escalation when needed
Industries
Where we focus.
We work best where daily operations depend on documents, approvals and company knowledge. The areas below are where we usually start, not the limit of what we build.
Healthcare and life sciences
Pharma, consumer health and medtech teams working under quality and regulatory requirements.
Typical areas
- Quality and regulatory operations
- Commercial and marketing operations
- Knowledge and documentation
Consumer brands and e‑commerce
Brands that sell directly and need marketing, service and operations to keep pace.
Typical areas
- Marketing and content
- Customer service
- Commerce operations
Other regulated operations
Mid-market teams outside health with the same pattern: documents, approvals and audit requirements decide whether AI sticks.
Typical areas
- Compliance tracking
- Review and approval workflows
- Knowledge and documentation
How we work
From business priority to a working system.
We agree what the system needs to do, how it will fit into your operation and how to judge whether it is working.
Engagement
Two ways to work with us
Every engagement starts with a conversation about fit. We then scope the work around your workflow, data access and integration requirements before proposing a price.
Models & providers
Powerful models are widely available. We choose them around your workflow, data requirements and operating costs, then connect them to the systems your team uses.
The operating layer
The model is one component. We build the system around it.
We connect AI to the systems your team already uses. The architecture depends on your data, permissions and the actions the workflow needs to perform.
Context
Connect the knowledge, data and history the workflow needs.
Action
Connect the tools where work gets done.
Learning
Evaluate quality, adoption and business effect, then improve the system.
From the blog
Notes on putting AI to work.
All posts →
How-to
·
AI literacy under the EU AI Act: what Article 4 asks of your company after the Digital Omnibus
Article 4 still applies after the Digital Omnibus, but no certificate is required. Who needs AI literacy training, what to cover and what to record.
Read article →
Opinion
·
Workslop and botsitting: why AI isn't saving your team the time you expected
AI saves individuals real time, then the team spends much of it checking, fixing and forwarding output that only looks finished. Here is where the hours leak, a five-day audit to find it in your own team, and the workflow changes that stop it.
Read article →
Common questions
Common questions
What does Postmodel actually build?
Custom AI applications, operational and commercial workflows, knowledge systems and integrations around a defined business need.
What type of companies are a good fit?
A good fit has a recurring process or a clear application need, a responsible owner, access to the relevant information and systems, and a team ready to implement a change. Our experience includes operational and commercial work in healthcare and life sciences.
Do we need to replace our existing tools?
We start with your existing tools and assess what can be connected. Any changes needed are identified during scoping.
What does our team have to do?
Provide a workflow owner, access to relevant information and systems, and feedback during design and testing.
How do we start?
Send a short project enquiry describing what you want to change. We start with a conversation about fit and, where there is one, propose a defined project scope.
How do you handle sensitive or regulated data?
We define data access, hosting, permissions and review requirements with the relevant IT, security and compliance stakeholders during scoping.
Where does the data live?
We agree where data is stored and which services may process it before implementation.
Do you integrate with our existing systems?
We assess the required connections and available interfaces, including legacy systems, before confirming the implementation scope.
Which models do you use?
We select models according to the task, data requirements, quality and operating costs.
Do you also build your own products?
Yes. Alongside client work, we develop our own applications on the same foundations. Client systems and client data always remain with the client; nothing from a client project goes into our own products.
What does an implementation project cost?
Pricing depends on scope, data access and integrations. We define the work before proposing a price.
How is an ongoing partnership priced?
It depends on the agreed operation, support and development responsibilities.
Do we own what you build?
Ownership, access, hosting and responsibilities are agreed in the project scope. Third-party software and services are identified separately.
Are there ongoing costs after launch?
Hosting, model usage, third-party services and any continuing support are identified in the proposal.
How do you measure whether it worked?
We agree the baseline, success criteria and measurement approach before building, then evaluate real use after launch.
Start here
The advantage goes to those who start.
Everyone has the same models now. The companies that put them to work first will be hard to catch. Tell us where to start.
Book a fit checkFree, 20 minutes. Within 48 hours after the call you get a one-page Workflow Map: what AI takes over, the rough time saved from your own numbers, and the next step, or an honest “not worth it”.