AI forecasting
AI and predictive analytics that forecast from your dataand your team reviews the numbers.
We build AI and predictive analytics on your own data: demand, inventory, staffing and cash-flow forecasts, delivered in the reports and tools you already use. Tested on past results, reviewed by your people.
30 minutes. You leave knowing which 3 processes to automate first and what they cost you today.
Illustrative example
Trusted by companies worldwide
Trusted by companies worldwide: Braffess, Casa Sors, HollaBoo, Laoom, Guardian Development Group
Results
Real systems, measured results.
Forecasting starts with the same step: find the work that costs most, then measure what changes.
Government contracting
Proposals cut from 60 hours to under one.
A federal contractor bidding on $10M+ contracts could only submit 3–4 proposals a quarter, because each one took about 60 hours to assemble by hand. We built an AI workflow that pulls past performance, checks compliance and formats to spec, so the team now submits 12+ a quarter.
<1 hper proposal, down from ~603xproposal capacity+23%win rateSaaS / Software
85% of support tickets resolved by AI.
A SaaS company with 50,000+ users had its best agents answering the same questions all day, and customers waited two hours for a reply. We built an AI assistant trained on their past tickets that answers instantly and hands complex cases to a person with full context.
1,200+agent hours back every month<5 sfirst response, down from 2 h+45%customer satisfactionInsurance
Claims processed 75% faster.
A regional insurer's adjusters spent 70% of their time on routine claims, so every claim took 15 days. We built an AI that reads the documents and photos, checks the policy and recommends a decision, so adjusters only handle the complex cases.
600+hours back every month99.5%decision accuracy+30%capacity, no new hiresE-commerce / D2C
Every lead contacted in under 20 seconds.
A home goods brand spending $40K a month on ads took 6–12 hours to reply to new leads, so many bought elsewhere. We built an AI system that replies by SMS, email or voice call within 20 seconds, day or night.
+34%conversion rate−28%customer acquisition cost100%of leads contactedLegal services
Manual invoice entry eliminated.
A boutique law firm's paralegals spent a quarter of their time retyping invoices, so billing ran late. We built an AI assistant that reads every invoice, matches it to the right case in Clio and syncs it to QuickBooks.
40+hours back every month99.8%data accuracy50%faster billing cycle
The problem
Plans built on last month's guess.
63%
of respondents using AI in supply chain management report revenue gains.
< 5%
is the most common size of the revenue increase reported.
Orders, stock, staffing and cash all depend on a number about the future. Most teams still build it by hand in a spreadsheet.
- Manual forecasting: Someone rebuilds the forecast in a spreadsheet each cycle.With AI forecasting: The forecast refreshes from your data on a schedule.
- Manual forecasting: Demand, stock and staffing plans come from separate files.With AI forecasting: One set of numbers feeds demand, inventory and staffing plans.
- Manual forecasting: Nobody knows how well last quarter's forecast held up.With AI forecasting: Every forecast is tested against past results and compared with actuals.
- Manual forecasting: A surprise shows up only after the month closes.With AI forecasting: Big changes are flagged early for a person to look at.
Better forecasts mean calmer planning decisions.
What we automate
What the system does every forecast cycle.
Gathers your data
Pulls sales, orders, stock and finance data from the systems you already use.
Cleans it
Flags gaps, duplicates and odd values before they reach the forecast.
Runs the forecast
Builds demand, inventory, staffing or cash-flow projections from your history.
Tests on past data
Checks the method against what really happened in earlier periods.
Delivers it
Writes results into your reports and tools, with changes highlighted.
Hands over to people
Your team reviews the numbers before any decision is made.
Is it time?
Signs it's time to forecast with AI.
Signals you need this
- Your forecast lives in a spreadsheet one person maintains
- Stock runs out or piles up because demand was misjudged
- Staffing and cash plans are redone by hand each month
- You have years of sales or order data nobody uses
- Teams plan from different numbers for the same question
When not to invest yet
- You have little or no historical data to learn from
- Your sales are a few large one-off deals each year
- Your data sits in paper files or no system at all
What you get
From your data to a working forecast.
- A map of how you forecast today, with the hours and dollars it costs you
- A fixed-price proposal with exact scope and timeline, before anything starts
- AI and machine learning forecasts built on your own data, such as demand, inventory, staffing or cash flow
- Backtesting: each forecast is tested on past data before you rely on it
- Results delivered in the reports and tools your team already uses
- Review steps where your people check the numbers before decisions
- Everything we build is yours: code, accounts, prompts and data
How it works
The Payback Loop. Five steps. Each build pays for the next.
We don't start with the AI. We start with the money.
Consulting
We find the manual work in your company and how many hours each task eats every week.
Process mapConsulting
We put a dollar figure on each process and rank them by payback. You see what to automate first, and what to leave alone.
AI roadmap, ranked by paybackImplementation
We build the first system on the tools you already use. Nothing new for your team to learn.
A working systemImplementation
We test it end to end before launch. It doesn't go live until it works without errors.
Tested, system liveSupport
The first build pays back fastest, so its savings fund the next one. Back to the map, and we keep every system running.
Monthly support (optional)
↺ Back to Map
Consultancies stop at the roadmap. Freelancers build without one. The loop only works when one team runs all five. You approve, we execute: about an hour a week from you.
FAQ
Questions about AI forecasting.
- AI and predictive analytics use your historical data to estimate what is likely to happen next, such as demand, stock needs or cash flow. The output is a forecast your team reviews and acts on.
- Machine learning finds patterns in your past data, such as seasonality and trends, and uses them to project forward. Each model is tested on earlier periods before it is used for planning.
- We test it on past data. One standard method is rolling origin evaluation, which moves the forecast start date across history to create multiple test periods. Your team also reviews the numbers.
- AI-powered demand forecasting can cover product demand, inventory levels, staffing needs and cash-flow projections. We pick the forecasts where better numbers change a decision you make often.
- Yes. A model can be close to actuals yet consistently overestimate. Researchers track forecast bias with a sign to show the direction of errors, so we check that too.
- You need historical data in a system, such as sales, orders, stock or finance records. We look at your data on the free 30-minute AI diagnosis and tell you whether it supports a forecast.
- We don't promise accuracy figures. Forecasts are tested on past data and reviewed by people. Survey data shows gains vary: the most common revenue increase reported with AI is under 5%.
- No. We build on the tools you already use and deliver forecasts into your current reports. You own everything we build, and optional monthly support keeps it running.
Final step
Pick a time. Let's talk.
You leave knowing which processes to automate first and what each one costs you today, whether we work together or not.
You can keep paying for manual work, or find out this week exactly what it costs you.
What happens on the call
Before
You answer 3 quick questions when you book, so we come prepared.
On the call
We find the manual work that costs you most and put a number on it, live.
Decide
An honest read on whether we're the right fit. If we're not, you'll hear it on the call.
Once you book, we look at your site and tools before the call, so the 30 minutes go to your numbers, not introductions.
Prefer to write first? Email us directly: contact@nexumautomations.com