Embed AI forecasting and decisioning into your product
Introduce forecasting and optimisation as native capabilities inside your platform, aligned to your product and user workflows.
Proprietary models, continuously improved
Access models trained and refined across workforce, inventory and production use cases, without building and maintaining them in-house.
Proven UI patterns
Accelerate delivery with established UI patterns, workflows and user journeys designed around forecasting and decision-making.
Commercial models
Introduce AI as a monetisable capability, with support on packaging, pricing and driving expansion revenue.
Adopt at your own pace
Start with a single use case and expand into additional capabilities over time. Our engines are modular, allowing you to align adoption with your product roadmap.
Make your product the system of decision
Embed forecasting and decisioning into your platform so your customers can plan and act directly within your product, reducing reliance on external tools.
Avoid building and maintaining it yourself
Deliver these capabilities without investing in data science teams, model development and ongoing maintenance across multiple use cases.
Partner journey
Sandbox
Validate payloads, run first forecasts, and confirm data mapping.
1
Pilot
Prove accuracy and operational usability with one customer / segment.
2
First customer live
Launch the AI module inside your product.
3
Scale
Roll out across install base, add more engines over time, and widen the use cases you support.
4
Ongoing partner success
Partner events + enablement, continuous AI engine improvement, and ongoing optimisation of the integration and UI
Partner success covers onboarding, technical enablement and ongoing commercial support. Practically this means: design workshops, payload reviews, help with sandbox testing, assistance with your first customer pilots, and regular check‑ins to tune performance and look for expansion opportunities across your customer base.
We can create bespoke configurations, model ensembles or pipelines for strategic partners, especially when there is a unique data source or decision problem that can be generalised. Any bespoke work is discussed during scoping and priced appropriately.
Partner-specific exogenous data is a dataset the partner makes available across all of their customers because it is broadly relevant to that partner’s vertical, region, or operating model. It behaves like platform exogenous data (shared and reusable), but it’s specific to that partner ecosystem.
The site provides a structured bank of FAQs, example JSON payloads, technical integration guidance, and UI reference materials to support rapid implementation. It’s designed so partners can answer most questions without waiting for synchronous support, while still having clear “next steps” when a live scoping call is useful.
A common approach is:
Use the FAQs to confirm product decisions and integration scope
Use JSON examples to generate payload builders and validators
Use UI wireframes to generate front-end backlog items and acceptance criteria
Use error/status patterns to generate automated tests and monitoring checks
The partner site content is designed to support that “prompt → build → validate” loop.
Yes. The site is intentionally designed to be “LLM-friendly”: content is structured, copy/pasteable, and written so it can be safely used as context for ChatGPT/Gemini during scoping, coding, and testing. This makes it easier for your team to generate payloads, build integration steps, write test plans, and troubleshoot errors using your existing AI-assisted development workflow.
Yes, for high‑value opportunities we can prioritise bespoke configurations, including partner‑specific exogenous datasets or domain‑specific models, provided there is a clear business case.
We agree the commercial model with each partner based on your pricing metric, go‑to‑market strategy, the engines you adopt, and how you want to package AI. The structure is consistent (pricing metric + agreed minimum AI uplift + 50% share + platform minimum floor), but the exact Y and the attribution approach are tailored to your business model.
TL;DR
SolvedBy.AI partners with B2B SaaS vendors to embed monetisable AI forecasting and decisioning directly into their products. We provide proven AI engines, UI patterns and a clear commercial model, guiding partners from sandbox and pilot through to scaled rollout. You keep the product, workflows and customer relationship; we continuously improve the AI layer and support long-term partner success.
