Software that puts the model in front of the decision-maker
A model in a notebook changes nothing. We build the web applications, APIs and products that bring analytics and AI into daily work, from a pricing tool for category managers to a full SaaS platform. We know the work because we run our own product, DCHire.
What we deliver
Decision applications
Purpose-built tools for planners, pricers and marketers, with the model underneath.
- Pricing and planning tools
- Scenario simulators
- Approval workflows
SaaS product development
From idea to a live, multi-tenant product with logins, roles and billing.
- Product discovery and UX
- Multi-tenant architecture
- Launch and iteration
APIs and integrations
Connect models and data to CRM, marketing automation and internal systems.
- REST and event APIs
- Salesforce, Marketo and Adobe integrations
- Secure data exchange
Embedded analytics
Dashboards and insights inside your own product or portal.
- Embedded BI
- Customer-facing reports
- Usage analytics
Cloud and DevOps
Reliable deployment, monitoring and cost control.
- CI/CD pipelines
- Containers and infrastructure as code
- Observability
Modernising internal tools
Replace fragile spreadsheets and legacy apps with maintainable software.
- Spreadsheet-to-app conversion
- Legacy rewrites
- Access control and audit
DCHire, our own SaaS product
DCHire is a hiring platform where companies share their experience of candidates, so they can identify genuinely keen candidates and avoid unethical practices. We took it from idea to a live, multi-company product, and we run it today.
We choose the stack around your team and platform, so you can run it after we hand it over.
Related case studies
An automated pricing tool for 90,000 SKUs across 2,000 stores
Elasticity models and a pricing framework that replaced gut-feel pricing, tested in market before rollout.
Read the case study →An automated inventory planning tool for 100,000 SKUs
Weekly SKU-market ordering driven by forecasts, safety stock and vendor lead times.
Read the case study →Hiring store staff at the right time for peak season
Department-level demand models that told a retailer when, and whom, to hire for peak season.
Read the case study →Have a decision you want to get right?
Tell us the decision, the data you have and the timeline. We will come back with how we would approach it.