AI Agent Development Company in Stockholm

The number follows what you actually build: a scoped production agent (customer support, internal copilot, document extraction), larger multi-agent systems with custom tool ecosystems, complex orchestration, and EU AI Act high-risk documentation, or ongoing optimisation, prompt iteration, and evaluation maintenance. Scope drivers include discovery, build, evaluation harness, red team, monitoring, and shadow deployment.

The EU AI Act came fully into force across 2025 to 2027, and Stockholm enterprises (especially the Klarna, SEB, Ericsson tier) are running classification audits across their entire AI estate. Our discovery phase produces a written EU AI Act classification per agent. Customer service and information retrieval agents are typically limited-risk, requiring transparency obligations only (the user must know they are interacting with AI). Agents touching credit decisioning, hiring, education access, biometric ID, or critical infrastructure are high-risk and require conformity assessment, technical documentation, risk management system, data governance, human oversight, accuracy and robustness controls, and CE-mark equivalent registration. We deliver the technical documentation pack aligned with Annex IV when high-risk; legal sign-off and notified body engagement remain with your in-house counsel.

Yes, and we deliberately study the Klarna deployment because it is one of the few European agent projects with published operating numbers (2.3M chats in first month, 700 FTE equivalent, 25 percent faster resolution, parity CSAT). The architecture is well-understood: an OpenAI-based assistant with retrieval over the Klarna knowledge base, tool calls into Klarna's order, payment, and refund systems, multilingual support (23 languages, mostly through native model capability), and human handoff for complex cases. We replicate that pattern at Stockholm SMB and mid-market scale using OpenAI Assistants or Claude with tool use, a smaller retrieval corpus (typically 5,000 to 50,000 documents), and integrations with Zendesk, Intercom, or Front. Realistic Stockholm SMB results are 40 to 60 percent contact deflection in first six months, with CSAT within 5 points of human baseline.

Stockholm's data protection authority IMY (Integritetsskyddsmyndigheten) has been one of the more active GDPR enforcers in the EU, with rulings against Klarna, Spotify, and Tele2 on consent, access requests, and data minimisation. Our agent builds include a written Data Protection Impact Assessment (DPIA) before any personal data flows into the LLM, a documented lawful basis (usually legitimate interest for B2B, consent for sensitive B2C), retention limits enforced at the storage layer (pgvector or Pinecone TTLs), and a Right to Erasure pipeline that purges both vector embeddings and conversation logs on request. We also document Schrems II transfer impact assessments for any non-EU model provider, and prefer Azure Sweden Central or self-hosted models when sensitive PII is in scope to avoid cross-border transfer entirely.

Stockholm gaming studios (King, Mojang, Paradox, Avalanche, Embark) typically deal with multilingual player support at huge volume, in-game purchase and refund disputes, abuse and toxicity reports, COPPA-aligned minor protection, and live-ops content questions. Our gaming agents are built on Claude or GPT-4o with tool use into Helpshift, Zendesk, or AppsFlyer for player lookup, refund APIs, and ban-list services. Retrieval covers patch notes, FAQ, and known issue databases. We hard-code EU DSA obligations (clear reporting and appeal mechanisms), COPPA protections (no PII retention from confirmed-minor users, automatic human escalation), and Apple and Google app store dispute timelines. Deflection in production runs 50 to 70 percent on common L1 tickets, with the agent handing off cleanly to human support for refund decisions above a threshold.

Yes. Klarna, Trustly, Avanza, Nordnet, SEB, Handelsbanken, and Swedbank all operate under Finansinspektionen (FI) supervision, with overlapping rules from EBA Guidelines on Outsourcing, DORA (the EU Digital Operational Resilience Act, fully applicable since January 2025), the EU Consumer Credit Directive, and PSD2. Our fintech agents stay inside EU regions (Azure Sweden Central or self-hosted Mistral in eu-north-1), produce DORA-aligned ICT third-party risk documentation, ship with the technical resilience and incident reporting controls FI inspectors expect, and document EBA outsourcing notifications when the agent qualifies as a critical or important function. Output logging feeds existing SIEM and model risk management platforms. We have shipped under these constraints and welcome FI inspection-readiness reviews as part of scope.

Prompt injection is now the OWASP LLM Top 10 number one risk and has caused public incidents at Stockholm-relevant peers (the DPD chatbot incident, the Air Canada hallucination case, the Chevrolet of Watsonville $1 truck case). Our defence stack runs in four layers: input validation and PII redaction before the prompt reaches the model, system prompt isolation with structured tool schemas (Claude tool use and OpenAI function calling rather than string-based prompting), output filtering with both regex and a smaller LLM acting as a referee, and a behavioural evaluation harness with at least 100 adversarial test cases including known jailbreaks (DAN variants, Crescendo, prompt leaking, indirect injection via retrieved documents). We red-team every agent before production and re-run the harness after every prompt or model change.

Yes. Stockholm enterprise stacks tend to standardise around Microsoft 365 (Teams, SharePoint, Azure AD), Salesforce or HubSpot for CRM, ServiceNow or Jira for ITSM, SAP or Visma for ERP and finance, and either Workday or BambooHR for HR. Our agents integrate through documented connectors (Microsoft Graph, Salesforce APIs, ServiceNow Table API, Jira REST, SAP OData) with proper OAuth scoping and least-privilege service accounts. For Klarna and Spotify-style operations we have built custom tool layers against internal microservices, with mTLS and short-lived JWT auth. Tool schemas are versioned and tested, every tool call is logged with input, output, latency, and cost, and we provide a runbook for tool failures that distinguishes between agent error, integration error, and downstream system error so on-call engineers can triage in under two minutes.