Solution: Forecasting dashboards
You guess at stock levels and pay for it both ways
We build forecasting dashboards from your own sales history that show what you are likely to sell, what to reorder and when, with the uncertainty shown honestly.
Sounds familiar?
Signs this is costing you time
Too much stock ties up cash and space. Too little loses sales and customers. Most small and mid-sized businesses manage this balance with experience, a spreadsheet and a lot of guessing. That works until the product range grows, sales channels multiply or the person who knows the numbers is away.
Forecasting does not need to be complicated to be useful. A clear view of trends, seasonality and lead times already beats guesswork.
The goal is not to hand buying decisions to software. It is to give the person who buys a clear, current picture every week, so their experience is spent on judgment calls instead of adding up numbers.
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Best sellers run out while slow items fill the shelves.
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Cash is tied up in stock that will not sell for months.
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Seasonal peaks catch you unprepared every year.
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Reorder decisions live in one person's spreadsheet.
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Online and in-store stock are managed separately.
Before and after
How it works today, and how it works after
How it works today
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Stock is checked by hand or in several systems.
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Reorders are based on gut feel and last year.
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Supplier lead times are remembered, not tracked.
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Stockouts are discovered by customers.
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Slow stock is noticed at the annual count.
How it works after
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Sales and stock from all channels flow into one place daily.
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Forecasts show expected demand per item, with a range.
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Reorder suggestions account for lead times and safety stock.
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Alerts flag items likely to run out soon.
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Slow movers are highlighted for promotions or clearance.
What we build
What we build
Sales and stock connections
Forecast models
Reorder logic
Dashboard
Alerts
In practice
What it looks like in practice
An illustrative walk-through, not a client story.
An online retailer with a physical shop sells around eight hundred products. The owner reorders by checking the store dashboard every few days and remembering which suppliers are slow.
The new dashboard combines online and in-store sales and shows, for each product, expected sales for the next eight weeks with a likely range. Products that will run out before the next delivery could arrive are flagged in red, with a suggested order quantity. Twenty slow-moving items are listed for a promotion. The owner reviews the suggestions each Monday, adjusts a few based on upcoming events the data cannot know about, and places orders.
Models and tools
AI models and MCP servers that usually fit
We choose models by task, data sensitivity and cost, and test them on your real examples before we commit. These are common starting points, not a fixed recipe.
How we build it
The services behind this solution
Most solutions combine two or three of our services. These are the ones this one usually needs.
Dashboards and reporting
Dashboards that pull numbers from the systems you already use and show what matters without a spreadsheet.
Database design
Data models that stay fast and correct as your business grows, with backups and access rules in place.
API integration
Make two systems share data reliably, with retries, logging and alerts when something goes wrong.
Industries where it fits best
Honest limits
Limits and human checks
Forecasts are estimates, not promises. They work best for products with enough sales history and stable patterns. New products, one-off events and sudden market changes are hard for any model to predict. We show forecast ranges, not single numbers, and make it easy for people to adjust suggestions using what they know.
Data quality matters more than model choice. Returns, stock corrections and missing sales records can distort forecasts, so the first part of the project is usually cleaning and combining data. AI language models play a supporting role, such as explaining changes in plain language; the forecasts themselves come from models suited to numbers.
Keep exploring
Services, industries and case studies
Related services
View all related services- Dashboards and reporting Dashboards that pull numbers from the systems you already use and show what matters without a spreadsheet.
- Database design Data models that stay fast and correct as your business grows, with backups and access rules in place.
- API integration Make two systems share data reliably, with retries, logging and alerts when something goes wrong.
- Ecommerce websites Online stores with clean product catalogs, simple checkout and the integrations that keep orders moving.
- Computer vision Software that reads photos and scans: damage checks, stock counts, document capture and quality control.
- Admin panels The back-office screens your team uses to manage users, content, orders and settings without a developer.
Solutions
View all solutions- Automated reporting Reports that build themselves from your systems on schedule, with a plain-language summary of what changed.
- Payroll automation Turn pay rules, attendance and leave into tested software so the monthly run becomes a review and payslips go out in one batch.
- AI automation and integrations Connect the tools you already use so data moves once, correctly, and AI reads the parts that arrive as text or documents.
- Price monitoring Collect competitor prices automatically, match them to your products and alert you when something changes.
- Feedback analysis Read every review, survey and ticket, group them by theme and sentiment, and show what customers keep asking for.
- AI sales research agent Short, sourced briefings on each prospect before a call, drafted by an AI agent from public information and your CRM.
Industries
View all industries- Retail Stock forecasting, sales dashboards, feedback analysis and store tools for retailers with shops and online sales.
- Ecommerce Online stores, product data cleanup, support assistants, price monitoring and order automation for online retailers.
- Manufacturing Quality inspection, production dashboards, quoting tools, knowledge assistants and legacy system modernization for manufacturers.
- Finance and accounting Client portals, document collection, invoice and receipt processing, and reporting for accounting firms and finance teams.
- Logistics and transportation Driver apps, order and shipment tracking, document processing and integrations for logistics and delivery companies.
- Construction and facilities Job tracking, maintenance requests, inspections, quotes and proof-of-work photos for builders and facility teams.
Case studies
View all case studies- Fashion deal aggregator Sale items from more than thirty brands are collected every night and classified consistently by a three-stage pipeline.
- Vacation rental operations system One calendar per property, cleaning tasks created from bookings, and owner statements built from the same records.
- Beach rental booking system A long-running booking system kept earning while it was extended, tested and given a safe, gradual path to a modern stack.
Guides and articles
View all guides and articles- How to set up automated reporting Replace manual weekly and monthly reports with dashboards and summaries that update themselves.
- How to connect AI to your database safely Let staff ask questions of your data in plain English without risking production systems or sensitive records.
- PostgreSQL vs MySQL The two most popular open-source databases compared for business applications.
AI models
View all ai models- Reasoning Models that think through multi-step problems before answering: analysis, planning, math, complex documents and agent work.
- Gemini 3.1 Pro Google's most advanced Gemini model for reasoning, software engineering and agent work, reading text, images, audio, video and PDFs. Available as a preview.
- Claude Sonnet 5 Anthropic's balance of speed and intelligence: a strong everyday model for assistants, document work, tool calling and coding.
- Claude Fable 5.1 The top tier of the Claude family, for the most demanding reasoning and long-horizon agent work, priced above Opus.
- Claude Opus 5.5 Anthropic's recommended starting point for most serious work: long-running agentic coding and knowledge work, with a 1M token context window.
- Gemini 3.8 Flash Google's most capable Flash model, stable since September 2026, for agents, software engineering and enterprise workflows with full multimodal input.
MCP servers
View all mcp servers- Ecommerce Servers that connect AI to online stores and marketplaces, for products, orders, customers and store content.
- Databases Servers that let AI query and, where allowed, change data in SQL, NoSQL, analytics and vector databases.
- Shopify Dev Shopify's Dev MCP server helps developers build for Shopify: it searches Shopify docs and API schemas and validates GraphQL, components and themes.
- PostgreSQL Lets AI assistants explore a PostgreSQL database, run SQL in a restricted read-only mode and check query performance and database health.
- Google Sheets Google's own Sheets MCP server lets AI read and update cell values and formulas, change spreadsheet structure and insert rows or columns.
- BigQuery Google's remote BigQuery MCP server lets AI list datasets and tables and run SQL, with a read-only query tool and IAM controls.
Glossary terms
View all glossary terms- Machine learning Machine learning is a way of building software that learns patterns from data to make predictions or decisions, instead of following only hand-written rules.
- Database A database is an organized store of data that software can search, update and keep consistent, such as customers, orders or bookings.
- Inference Inference is the step where a trained AI model is used to produce an output, such as an answer, a label or a prediction, from new input.
- Vector database A vector database stores embeddings, lists of numbers that represent meaning, and quickly finds the ones most similar to a query.
FAQ
Questions about forecasting dashboards
Have a question that is not here? Ask us directly.
Ideally at least a year for seasonal patterns, but useful forecasts can start with less for fast-moving items. New products use similar items as a guide.
Yes, most ecommerce platforms and POS systems have APIs we can use. See API integration.
No. It works alongside your inventory system, adding forecasts and reorder suggestions. We can also build or integrate full inventory tools if needed. See dashboards and reporting.
It can, but we recommend suggestions reviewed by a person at first. Automatic orders make sense once forecasts have proven reliable for specific items.