AI and software for growing businesses, built on the systems you already run and handed over to your team at the end.
Each of these is a first job on its own. None of them needs a programme to get started.
In brief
EigenSpark builds AI systems and the software around them for growing businesses. You name the job that costs you the most time: chasing payments, quoting, reconciling invoices, answering the same customer questions, or keeping vendor records straight. We build it on the tools you already pay for, run it in your own account, and hand it to your team with the documentation and the training to keep it going.
What we cover
The same obligations as a large company, with far fewer people watching them.
The starting position
No spare capacity, too much in one person’s head, and systems that do not talk to each other.
No data team, no centre of excellence, no eighteen-month roadmap. Whatever gets built has to work without a dedicated person watching it.
Which customer gets which rate, why that supplier is on hold, what was promised two years ago. It works until they go on leave.
Accounting here, orders there, stock somewhere else, and the joins done in Excel every month. Assembling an answer costs a week.
Payment ageing, e-invoice windows, filing dates. Each one is small, each one has a cost, and they live in the same overloaded spreadsheet.
How an engagement runs
One job, on your existing systems, handed over at the end so you stop needing us.
We take a single job with a clear before and after: the payment exposure view, the reconciliation, the quotation drafter. Scoped so it goes live in weeks and so one job pays for itself.
Tally, Zoho, Busy, SAP Business One, a spreadsheet, email, WhatsApp. Nothing gets replaced, and we work with whoever supports what you have today.
The code, the documentation and the account are yours, and your own people are shown how it works while it is being built. If you want a second job done later, that is a new decision.
Use cases
Money and compliance, then sales and customers, then operations, then the back office.
Your vendor master classified against Udyam registration, ageing tracked on the right clock per vendor, and the exposure shown daily while you can still act on it.
Continuous Compliance Monitor →Purchase invoices matched against what your suppliers actually reported, with mismatches and late filings flagged in the week they happen, and the working shown.
Continuous Compliance Monitor →Duplicate vendors merged, registration details verified and enterprise status captured at onboarding, so the payment clock is built on a master you can trust.
Data Engineering & Platforms →Enquiries read against your price list, past quotations and standard terms, and returned as a draft with the assumptions and the margin shown, for you to send.
Generative AI →A name and a company turned into a usable profile from public sources, with a confidence score, so a small sales team spends its week on the calls worth making.
Lead Enrichment Agent →An assistant that answers order, product, warranty and billing questions from your own documents and the customer’s history, and hands anything unusual to a person.
Generative AI →Customer and supplier contracts read into a register of obligations, renewals, penalties and price terms, with every change from your standard tagged by severity.
Contract Risk Analyser →Outstanding invoices aged by customer and by reason, with follow-up drafted in your own tone and ordered by what is actually collectable, for a person to send.
Agentic AI →Real consumption, lead times and seasonality read into reorder points per item, with dead stock surfaced, so working capital stops sitting on the wrong shelf.
AI & Data Strategy →Invoices, purchase orders, receipts and challans read into your accounting system, with anything doubtful routed to a person, so data entry stops eating afternoons.
Document Intelligence Engine →Sales, purchase, stock, receivables and cash read from the systems you already run into one current view, so the tenth of the month stops being an assembly job.
Data Engineering & Platforms →Leave, reimbursement and policy questions answered from your own circulars, with the current version identified, so the same six questions stop reaching one person.
Generative AI →The engineering half
Four layers. The fourth is the handover, which is the one most vendors leave out.
Nothing here starts with replacing your accounting package. We read what it holds and leave it where it is.
Most of the value in a smaller business is in connecting three systems that already work separately.
Built for a specific person doing a specific job, with a review step wherever money or a customer is involved.
The account, the code and the documentation are yours. We build so that keeping it running costs little and needs nobody in particular.
We also run the training that goes with it: SQL and data engineering, cloud and enterprise systems, alongside the AI tracks. For a smaller team that is often the better investment, and we will say so.
What we offer growing businesses
Most companies your size start with a product, because it is the fastest first win.
The fastest way to start.
When the job needs building.
So your own people can carry it.
The person who owns the job.
Working in a specific function? See how we help Finance & Accounting teams.
Security and controls
A person approves anything that leaves. It runs in your account, and you own it.
Quotations, collection follow-ups and customer replies are drafted and reviewed before they go. Nothing is sent to a customer or a supplier on your behalf without somebody looking at it.
Your cloud account, your data, your access. When the engagement ends nothing has to be migrated, because it was never anywhere else.
Source, documentation and infrastructure definitions are handed over. Another firm could pick this up, and that is deliberate.
What it will cost to keep the thing running each month is part of the scope, agreed upfront. A system nobody can afford to run is a failed project.
FAQs
That is the usual assumption and it is worth testing. The engagements on this page are single jobs with a clear before and after, scoped to go live in weeks. The same engineers who build for banks and REITs do this work, because the underlying problem is the same one at a different size. The scope changes; the standard does not.
We will quote against a specific scope after a short conversation, and we will tell you when the job is too small to be worth doing or when a product you can simply buy would be cheaper than anything we would build. What we will not do is publish a number here that turns out to be wrong for your situation.
No, and we would push back on anyone who suggested it as a starting point. We read from what you already run and leave it in place. Migration is expensive, disruptive and almost never the reason the original problem existed.
Because it is live, dated and expensive, and most companies this size are managing it in a spreadsheet they look at near year end. Payment to a micro or small supplier delayed beyond 45 days is disallowed as an expense that year, which raises taxable income. Knowing your exposure daily, per vendor, while the year is still open, is worth more than most software a business this size buys.
It is built so that it needs nobody in particular. The system runs in your own cloud account, the running cost is agreed before you commit, and your own people are walked through it during the build. Source and documentation are handed over, so another firm could pick it up if you ever wanted them to.
Where a hosted model is used, exactly what is sent to it is agreed and written down before anything is built, and for several of the jobs on this page nothing needs to leave your account at all. Where the data is sensitive enough, open-weight models running in your own environment handle the work.
No, and the parts that are not are usually what makes the AI work. Connecting your accounting system to your order data, cleaning the vendor master and building one screen for one job are ordinary engineering, and they are most of the value. Some of the best outcomes on this page involve no model at all.
Yes, and for some companies that is the better answer. If you have a capable person who needs the skills, our training practice runs the AI, data, cloud and enterprise systems tracks that would get them there.
Related
The three products that make the fastest first job, and the pillars behind them.
Payment exposure, reconciliation and filing checks.
→ ProductInvoices and orders read into your accounting system.
→ ProductA thin enquiry turned into something worth calling.
→ FunctionThe function that owns most first jobs here.
→ PillarWhen the job needs to be built to your own requirement.
→ PillarGetting your own people able to run it.
→Describe it in a paragraph, and tell us what software you run. You get back a written assessment within 48 hours: whether it is worth building, whether something you can simply buy would do it cheaper, and what it would take.
Talk to us