POVAMSOLUTIONS

Consulting for a faster, simpler public sector

We find what to automate, show what it saves, and build it with you.

We connect new technology with how the public sector works

Innovation

New tools, automation and AI that save time and money

POVAMSOLUTIONS

We bring the two together

Public sector

Tenders, laws, budgets and how decisions really get made

We advise first, then we build

  1. Consulting

    01 Map

    We map how the work gets done today, with the people who do it

  2. Consulting

    02 Find

    We find what to automate, which tools to use and who does what

  3. Consulting

    03 Prove

    We calculate the benefit in hours, cost and payback time

  4. Implementation

    04 Build

    We build what we proposed, test it and train your team

We know how the public sector works

Good tools fail in the public sector when they ignore the rules. We plan every project around them.

  • We plan around tenders and buying rules.
  • We build to data, security and accessibility laws.
  • We time the work to budget cycles.
  • We bring staff along from day one.

Planning a tender?

Talk to us early. We help you write requirements that get you what you need.

Projects

Recent work for public bodies and companies. We keep client names private.

Manufacturing company

Quotes, invoices and stock checks ran on spreadsheets and email. Now quotes build themselves, and every supplier invoice is checked against what arrived.

National agency

Data arrived on paper, by email, in spreadsheets and from four systems. We brought it into one source of truth and connected records that had never been linked.

Public agency

We trained middle managers on AI tools and new software, then helped them hire people who could keep the change going.

Manufacturing company

The problem

Sales built every quote by hand, and finance chased documents by email. About 1,200 supplier invoices a month were paid without checking them against the goods received.

What we did

We generated quotes from a short form using the current price list, sent financial documents to the right people on schedule, and matched each supplier invoice to the goods received. AI reads the PDF invoices.

The result

Quotes take minutes instead of a day, and differences are caught before paying.

National agency

The problem

The same person or company looked different in every system, and reports took weeks.

What we did

We mapped every channel, digitized paper with AI and a staff check, set one standard format and ID, and cross-referenced the sources.

The result

One view per case, reports in a day, and duplicate records found.

Public agency

The problem

They had bought new tools that almost nobody used.

What we did

We ran hands-on courses with their own documents and tasks, wrote guides, defined new roles and helped run the hiring.

The result

Teams use the tools every week, the new hires are on board, and teams launch their own small automations.

AI Lab

Our deepest AI work: systems that change how a whole company runs.

A shared AI workspace for the whole company

One place where the company's knowledge, playbooks and AI agents live, so everyone's AI works from the same facts.

AI-native before a sale

We made a company AI-native ahead of its sale. Lower costs and less reliance on key people raised the multiple buyers paid.

A purchasing agent for a construction company

An agent runs purchasing from request to purchase order. It compares supplier quotes, and a person approves every order.

A shared AI workspace for the whole company

The problem

Everyone used AI on their own, without company context, and knowledge lived in people's heads.

What we did

We built a company wiki the AI reads first, shared playbooks for repeated tasks, agents with clear permissions, and a sync so every improvement reaches everyone.

The result

Consistent work, faster onboarding, and knowledge that stays when people leave.

AI-native before a sale

The problem

The owners planned to sell in 18 months, and buyers discount businesses that depend on their founders and on manual work.

What we did

We documented and automated the core processes, built AI into sales, operations and finance, and left clean data that buyers could audit.

The result

A higher margin, a valuation multiple that went from 5x to 6.5x EBITDA, and a shorter due diligence.

A purchasing agent for a construction company

The problem

Every job needed materials from many suppliers, and prices changed from week to week. Buyers spent their days asking for quotes by email and comparing them in spreadsheets.

What we did

We built an agent that takes each request from the site, asks the right suppliers for quotes, compares price, delivery time and past performance, and drafts the purchase order. A buyer approves it before it goes out.

The result

Orders go out the same day instead of taking three, and buyers spend their time negotiating instead of copying prices.

Tell us what slows you down

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