# Grejda AB

> Grejda AB takes over routine work in a company's business processes with AI agents that it builds and runs inside the client's own systems and environment. The first process goes live within 6 to 10 weeks, starting with a free prototype day.

## Uppslagsord: grejda

[ˈɡrɛjːda] *verb* grejdar · grejdade · grejdat

1. Få något gjort; ordna, fixa, klara av.
   *”Vi grejdar det.”*
2. Reda ut det trassliga och göra det redo.

Etymologi: Av fornnordiska *greiða*, ”ordna, reda ut, göra redo”, från urgermanska *\*garaidijaną*, ”ställa i ordning”. Jämför svenska *greja*.

## In short

Instead of handing a process to an outsourcer's staff, the client lets AI agents that Grejda builds, runs and improves do the routine work, inside the client's own systems. When an agent reaches the limit of what it can handle, Grejda's team takes over, so the client does not need to staff for peaks.

Grejda builds agents, not assistants. An assistant helps one person; an agent runs a whole process.

The first process is in production within 6 to 10 weeks and is measured against the same metrics before and after. Everything runs in the client's own environment, and the client can replace Grejda, so there is no lock-in.

## What we do (in Swedish)

- Vi tar oss an de svåra problemen så att ni ökar lönsamheten i kärnverksamheten.
- Vi sköter genomlysningen så att ni sänker kostnaderna för molnet.
- Vi sköter kapacitetsplaneringen så att ni sänker kostnaderna för molnet.
- Vi sköter fakturagranskningen så att ni sänker kostnaderna för molnet.
- Vi håller ihop orderflödet så att ni ökar lönsamheten för projekten.
- Vi håller ihop leveransplaneringen så att ni ökar lönsamheten för projekten.
- Vi håller ihop faktureringen så att ni ökar lönsamheten för projekten.
- Vi säkrar granskningen så att ni skyddar marginalen i varje avtal.
- Vi säkrar riskbedömningen så att ni skyddar marginalen i varje avtal.
- Vi säkrar förhandlingsunderlaget så att ni skyddar marginalen i varje avtal.
- Vi driver utvecklingen och underhållet så att ni höjer marginalen för tjänsten.
- Vi driver förvaltningen så att ni höjer marginalen för tjänsten.
- Vi driver kvalitetssäkringen så att ni höjer marginalen för tjänsten.
- Vi digitaliserar blanketterna så att ni sänker kostnaden för varje ärende.
- Vi digitaliserar pappershanteringen så att ni sänker kostnaden för varje ärende.
- Vi digitaliserar registreringen så att ni sänker kostnaden för varje ärende.
- Vi automatiserar provisioneringen så att ni höjer avkastningen på plattformen.
- Vi automatiserar miljöuppsättningen så att ni höjer avkastningen på plattformen.
- Vi automatiserar konfigurationen så att ni höjer avkastningen på plattformen.
- Vi tar hand om bevisinsamlingen så att ni sänker kostnaden för varje revision.
- Vi tar hand om efterlevnadsarbetet så att ni sänker kostnaden för varje revision.
- Vi tar hand om certifieringen så att ni sänker kostnaden för varje revision.
- Vi förbereder bokföringsbesluten så att ni höjer marginalen för varje kund.
- Vi förbereder momsbedömningen så att ni höjer marginalen för varje kund.
- Vi förbereder avdragsprövningen så att ni höjer marginalen för varje kund.
- Vi förebygger kompletteringarna så att ni sänker kostnaden för varje ansökan.
- Vi förebygger rättelserna så att ni sänker kostnaden för varje ansökan.
- Vi förebygger omprövningarna så att ni sänker kostnaden för varje ansökan.
- Vi tar över kundtjänsten så att ni sänker kostnaden för varje stängt ärende.
- Vi tar över reklamationerna så att ni sänker kostnaden för varje stängt ärende.
- Vi tar över leveransavvikelserna så att ni sänker kostnaden för varje stängt ärende.

## Business operations

Business operations are Grejda's primary focus: the routine work that keeps a company running and today passes between inboxes, documents and systems. Grejda starts where the same work happens often, in large volumes, and cannot wait. The agents read the incoming information, act in the client's systems and give the reasoning behind each decision, and Grejda's team handles the exceptions.

- **Case handling:** cases that start with an email, from the first message to the answer, with fewer handovers between people.
- **Bookkeeping:** an agent reads a receipt and produces the journal entries, the expense claim, the legal basis and the tax treatment, with its reasoning and the rules it cites.
- **Form completion:** an agent fills in a form through a conversation, using text, voice, PDFs and images, and then gives its decision with the reasoning behind it.
- **Project follow-up:** an agent tracks each project from order to final invoice. It reads the information in the project managers' inboxes, links it to the right project and order line, and flags what needs action.

## IT operations

The same model applied to IT, cloud and software delivery.

- **IT operations:** incident triage, alerts handled with runbooks, changes and patching, and capacity reports.
- **Cloud cost (FinOps):** agents that find cloud savings and act on them. In one deployment, an agent in production found savings of 9.2 million Swedish kronor a year.
- **Software delivery:** software factories in which coding agents such as Claude Code and OpenAI Codex document, write, review and test code under the control of the client's developers.

## Where agents pay off first

The best place to start is a process with high frequency, high urgency and high volume: the same work happens many times a day, it cannot wait, and it arrives in large numbers at once. These three examples come from one situation, an airline that cancels a flight with more than 300 passengers on board. They illustrate the pattern; they are not a client case.

- **Proactive outreach:** within minutes of the cancellation, a text and voice agent contacts every passenger by text message, email and phone, explains what has happened and what happens next, in the passenger's own language.
- **The inbound surge:** the wave of calls and chats that follows is answered at once, around the clock, from the live flight and booking data, so no passenger waits in a queue for an answer that is already out of date.
- **Rebooking and care:** the agent offers each passenger the next available flights and rebooks the choice in the booking system, arranges hotel and meal vouchers where the rules require them, and hands every case it cannot resolve to a person, with the full context.

## AI-ready data

An AI agent is only as good as the data it reasons over. Data that is clean and governed for reporting is usually not yet ready for an agent. Grejda refines the client's data into AI-ready data: structured, linked to its sources, traceable end to end and kept current, so that the agent, and the people who rely on it, can stand behind every answer. The work never finishes, because data goes stale.

- **Source-level citation:** every claim cites the exact passage it rests on.
- **Auditable lineage:** the sources and the reasoning behind an answer can be reconstructed months later.
- **The whole estate:** answers draw on contracts, wikis, tickets and SaaS systems, not only on the tables in the data warehouse.
- **Contradiction detection:** when two sources disagree, the conflict is flagged rather than silently resolved.
- **Continuous freshness:** when the data changes, the answers change with it, without a manual rebuild.

Grejda builds this refinement layer in the client's environment, with self-hosted open-source tools such as PageIndex (reasoning-based retrieval tied to the exact source passage) and OpenKB (a knowledge base that cross-links documents, flags contradictions and keeps itself current), or with hyperscaler services such as Google Knowledge Catalog. The tools are interchangeable; the client's data and the way it is refined stay with the client.

## How an engagement works

1. **Choose the process.** Frequent, urgent, high-volume work costs the most time and carries the most risk, so Grejda starts there, and with the information the agent will need.
2. **Prototype day, free of charge.** The client sees an agent working on its own process in one day. The client's team spends two hours, one before and one after the working day.
3. **Production in 6 to 10 weeks.** One workflow with minimal or no technical dependencies goes live in the client's environment.
4. **Grejda runs it, then the next process.** Further processes follow, one at a time.

Results are measured before and after: cases handled per day, how much gets completed, time from first email to answer, and how often a case changes hands.

## How Grejda runs the processes

Choosing a model is the visible tenth of an AI solution. The rest is the work that makes an agent run every day and resolve real cases, and Grejda takes it on:

- **Discovery and redesign:** mapping the workflow and rebuilding the process around the agent. The change management decides whether anything works at all.
- **Integration:** connecting the agents to the client's systems and data, in the client's own environment.
- **Context and memory:** grounding the agents in the client's knowledge with retrieval and long-term memory, so they remember a case across every contact.
- **Model orchestration and evaluations:** choosing, routing and fine-tuning models behind a set of evaluations on the client's own cases, with regression tests as the models change.
- **Attribution:** a record of what the agent did on each case, why, and which measure it moved.
- **Compliance:** controls for regulated workflows, audit trails and data residency.
- **Guardrails:** limits on turns, rate and budget, and checks that keep an agent on its task, so it is handed to a person before it loops or overspends.
- **Escalation:** Grejda's team handles what an agent cannot, in the client's own tools.
- **Token economics:** caching, batching, routing and trimmed context, so the cost per task falls as the volume grows.
- **Reliability (AgentOps):** tracing and monitoring of what each agent does, drift detection and evaluation of its results, so the quality holds over time.
- **Ownership:** everything runs in the client's environment, the data stays there, and the client can replace Grejda.

## AI platform, governance and gateways

Agents need a platform to run on and rules to run by. Grejda builds and runs both in the client's environment, on open-source software or on the services of the client's hyperscaler.

- **AI platform:** the runtime for agents and models, on Kubernetes, with open-weight models hosted on the client's GPUs and the hyperscalers' model services where they fit.
- **AI gateway:** one controlled entry point for all model traffic. It routes each request to the right model, holds the keys, enforces rate limits and budgets per team and use case, and logs every call, so use and cost are visible per task.
- **AI governance:** rules for which data and which models each agent may use, audit trails of every decision, and human approval where the process requires it, in place from day one.
- **Evaluations:** every agent and model is tested against the client's own cases before it goes live and after every change, so a better or cheaper model can replace the current one on evidence rather than on trust.

## Technology and platform

- **Models:** generative AI and large language models, including open-weight and open-source models hosted in the client's environment
- **Capabilities:** retrieval-augmented generation (RAG) over the client's own documents, speech-to-text and text-to-speech
- **LLMOps:** model hosting and serving on GPUs, monitoring, evaluation and cost control
- **Platform:** Kubernetes as the infrastructure abstraction of choice, platform engineering, AI observability
- **Hyperscalers:** Microsoft Azure, AWS, Google Cloud, Oracle Cloud Infrastructure
- **Sovereign clouds:** Evroc, Hetzner, Scaleway, UpCloud
- **On-premises:** VMware, OpenStack, Harvester

## From prototype to production

A vibe-coded prototype shows that an idea can work; an AI application in production does the work every day. Grejda builds the latter, and also takes prototypes that the client has built into production. Why AI often stalls after the prototype, and Grejda's answer:

- **The wrong problem:** start with a frequent, urgent, high-volume process
- **Missing data:** start with the information
- **It does not fit the workflow:** the agent works inside existing systems
- **Nobody runs it:** Grejda operates it in the client's environment
- **Cost and risk get out of control:** governance and measurement from day one
- **It is too hard for AI:** the prototype day tests it in a single day

## Track record

The team behind Grejda has delivered for regulated industries and global enterprises, including three data centre moves without downtime for the business-critical systems.

- **Collector Bank:** the entire data centre moved to Azure, meeting the requirements of Finansinspektionen (the Swedish Financial Supervisory Authority) and PCI DSS. Case published by Microsoft.
- **LiveArena:** from 2021 to 2026, the team took AI Producer, an automated live broadcasting service, from a prototype-stage startup to an enterprise-ready global SaaS. The work covered the code that runs and operates the service, the Azure infrastructure, the Kubernetes platform and day-to-day operations. AI Producer launched on Microsoft AppSource and Azure Marketplace, passed Microsoft 365 App Certification, and was tested at more than 800 nodes to run over 200 live broadcasts in parallel.
- **Norce (formerly Jetshop):** the largest e-commerce SaaS platform in the Nordics moved out of two data centres and into Azure in under six months, while it stayed live for its merchants. The work included changes to the application code, a move from on-premises Kubernetes to Azure Kubernetes Service, and storage for 30 million product images, with minimal to no downtime.
- **Ahlsell:** for a Nordic distributor with 17 billion Swedish kronor in turnover, 109 servers and 55 database instances (SQL Server, MySQL, PostgreSQL, Redis and Cosmos DB) moved to Azure ahead of a contract deadline. These databases run Ahlsell's e-commerce, analytics and warehousing, so operations and revenue stop if they are unavailable; the business-critical systems moved without downtime. The e-commerce core was also rebuilt on Azure platform services for Ahlsell's new in-house development team.

## Frequently asked questions

- **Is this a form of outsourcing?** Yes, but the routine work is done by AI agents, not by an outsourcer's staff, inside your own systems, and Grejda's team handles the exceptions. This is also known as AI-native BPO.
- **How quickly do we see value?** The prototype day shows an agent working on your own process within one day. The first agent is in production within 6 to 10 weeks.
- **What does the first step require from us?** Two hours of your team's time, one before and one after the working day. The prototype day is free of charge.
- **Where do our data and agents run?** In your own environment: any cloud, on-premises or a hyperscaler, on Kubernetes.
- **What if we want to stop working with Grejda?** Everything runs in your environment, so you can replace Grejda.
- **Who handles what the agent cannot solve?** Grejda's team takes over in your own tools, so you do not need to staff for peaks.
- **How do we know that it pays off?** The same metrics are measured before and after: cases per day, completion, time to answer and handovers.
- **Which processes should we start with?** Those with high frequency, high urgency and high volume, where the same work arrives in large numbers and cannot wait. A cancelled flight with 300 passengers is a typical example: outreach, the inbound surge and rebooking all happen at once.
- **Is our data ready for AI agents?** Ask five questions: does every answer cite its exact source; could you reconstruct its lineage six months from now; does it draw on contracts, wikis and tickets as well as the warehouse; does the system flag contradictions between sources; and does the answer change by itself when the data changes? A single no means the data is governed, but not yet AI-ready.

## Search terms

AI-native BPO, AI agents, agentic AI, agentic automation, AgentOps, generative AI, large language models, LLMOps, open-weight models, open-source models, model hosting, model monitoring, model evaluation, RAG, AIOps, FinOps, Kubernetes, platform engineering, sovereign AI, cloud migration, AI-ready data, AI platform, AI governance, AI gateway, LLM evaluation, voice agents, AI-konsulter, AI-konsult, AI-konsulter i Jönköping, AI services as software, services as software

## About

Grejda AB is an AI services-as-software company based in Jönköping, Sweden: it delivers business services through AI agents that it builds and runs, and solves problems that companies have all over the world.

- **Legal name:** Grejda AB
- **Org. no.:** 559601-6153
- **VAT no.:** SE559601615301
- **Founder:** Daniel Grenemark (https://www.linkedin.com/in/danielgrenemark/)
- **LinkedIn:** https://www.linkedin.com/company/grejda-ab
- **Allabolag:** https://www.allabolag.se/5596016153

## Contact

- Email: [hej@grejda.com](mailto:hej@grejda.com)