AI Agent Development Company

AI agents are autonomous software systems that can understand requests, make decisions, take actions, and interact with users and systems. Unlike simple chatbots that follow scripts, AI agents can handle multi-step tasks, access real-time data, make contextual decisions, and learn from interactions. They can operate across channels, chat, voice, email, and integrate with your CRM, ERP, and internal systems.

An agentic AI strategy defines how an organization deploys autonomous AI agents across customer-facing and internal operations. It covers: which processes benefit from agent autonomy, what level of human oversight is needed, how agents integrate with existing systems, how to measure agent performance, and governance frameworks for agent decision-making. It's about moving from AI-assisted to AI-autonomous workflows where appropriate.

A chatbot typically follows predefined conversation flows and can answer FAQ-style questions. An AI agent is fundamentally different: it can understand complex requests, access multiple data sources, make decisions, execute multi-step tasks, and handle exceptions. For example, a chatbot answers 'What are your hours?' while an AI agent can process a complete order, check inventory, apply discounts, and schedule delivery, all in one conversation.

We build three categories: 1) Customer-facing agents, for support, sales, and onboarding via chat, voice, and email. 2) Internal agents, for document processing, data analysis, report generation, and task management. 3) Orchestration agents, that coordinate between systems, route tasks, and manage complex multi-step workflows. Most projects combine elements from all three.

AI voice agents use speech-to-text, natural language understanding, and text-to-speech to handle phone conversations autonomously. They can answer questions, route calls, take orders, schedule appointments, and handle common inquiries. Modern voice agents sound natural, handle interruptions, and know when to escalate to human agents. We integrate them with your phone system and CRM.

It depends on the workflow. We agree the baseline before the build and report against that, rather than a standard deflection rate. The Ljusgårda order workflow is a named case on the case page. Across 100+ implementations the production rate is 96%.

Every agent includes: conversation guardrails and brand voice guidelines, escalation rules for complex or sensitive cases, real-time monitoring and quality dashboards, A/B testing for continuous improvement, audit logs for compliance. We test extensively before launch and maintain ongoing quality reviews.

Yes. We integrate agents with all major platforms: CRM (Salesforce, HubSpot), ERP (SAP, Dynamics), ticketing (Zendesk, Freshdesk), communication (Slack, Teams, WhatsApp), phone systems, and custom APIs. Agents can read and write data across systems to provide contextual, personalized interactions.

We start with core functionality, launch with human oversight, then expand from real conversation data. How long that takes depends on the systems the agent has to touch. We do not promise a go-live date before we have seen the workflow.

No. Agents take the routine, repetitive interactions so the team can spend time on the cases that need a person. The split is set per workflow, against the baseline you agree before the build, not a standard share of volume.

AI agent work covers use-case selection, conversation and journey design, integration with CRM, ERP and phone systems, guardrails, evaluation, human review, and monitoring. Alice Labs agrees the scope and the KPIs before kickoff. Across 100+ implementations the production rate is 96%.

An AI agent consultation is a working session where we review your customer-service, sales or back-office workflows, identify which steps are agent-suitable (high volume, repeatable, data-accessible), and outline a path. The brief names the baseline we will measure. We do not attach a standard deflection percentage.

Yes. We build custom AI voice agents for businesses across inbound support, outbound sales, appointment booking, order confirmation, surveys, and after-hours coverage. Our voice agents use modern speech-to-text and text-to-speech for natural conversation, integrate with your phone system (SIP, Twilio, Telnyx, Aircall, etc.) and CRM, and include barge-in, interruption handling, sentiment detection, and clean human handoff. We are an outcome-based agency, not a platform reseller, we own the build, the integration, and the KPIs.

A SaaS voice platform (e.g. Vapi, Retell, Bland, ElevenLabs Conversational AI) gives you tooling, you bring the design, integrations, prompts, evals, and ops. An AI voice agent agency like Alice Labs delivers the working agent end-to-end: discovery, build, integration, launch, and continuous tuning, with KPIs in your P&L. Agencies are the right choice when you want a production agent live in weeks with measurable cost-out, not a developer platform to staff up around.

Voice and conversational AI work combines which interactions to automate, and what success looks like, with designing flows, building the agent, integrating systems, and measuring outcomes. At Alice Labs the same senior team handles both. Across 100+ implementations the production rate is 96%.

Yes, we have built AI voice and chat agents for regulated industries including banking, insurance, and healthcare. Banking deployments require additional controls: strong identity and authentication flows, PII redaction in logs, full audit trails, GDPR and EU AI Act alignment, escalation to human agents for any complaint or vulnerable-customer signal, and red-team testing before launch. We design every banking agent assuming external audit from day one.

Yes. Alice Labs provides AI agents consulting for mid-sized and large companies: use-case selection, build or buy decisions, vendor and framework selection, evaluation harness design, and human-in-the-loop governance. Consulting engagements are led by the same senior team that runs the implementation. Across 100+ implementations the production rate is 96%.

Five things: (1) Production deployments with named clients, not just demos. (2) Native integration with your phone stack, CRM, and core systems. (3) Evaluation and monitoring infrastructure, if they cannot show you the eval harness, the agent will drift. (4) Clear escalation and human-handoff design. (5) A price and KPIs agreed before kickoff. Alice Labs publishes 100+ implementations and a 96% production rate.

An AI voice agent service is a productised offering that combines a large language model (GPT-4o realtime, Gemini Live, Amazon Nova Sonic), speech-to-text and text-to-speech (Whisper, Deepgram, ElevenLabs), telephony (Twilio, Vonage, Amazon Connect, Aircall), business logic and CRM integration, delivered either as a build-and-hand-off engagement or as managed voice agent operations where the vendor runs the agent in production against agreed KPIs.

Enterprise AI voice agent projects at Alice Labs typically run €60,000 to 120,000 for a build-and-hand-off deployment over 8 to 10 weeks, or €8,000 to 25,000 per month for managed voice agent operations on top of the build fee. Per-minute runtime cost has fallen roughly 70% in the last 12 months as realtime APIs matured; a typical Alice Labs voice agent runs €0.08 to 0.15 per minute all-in (model + telephony + hosting) at enterprise volumes.

In 2026 the credible evaluation set splits into three groups: (1) model providers exposing realtime voice, OpenAI GPT-4o Realtime, Google Gemini Live, Amazon Nova Sonic. (2) SaaS voice platforms, Vapi, Retell, Bland, ElevenLabs Conversational AI, which give you tooling but not delivery. (3) AI voice agent agencies like Alice Labs, which own the build, integration and KPIs end-to-end. The right choice depends on whether you have in-house AI engineering capacity or want an outcome delivered.

Yes. Alice Labs builds bilingual Swedish + English voice agents daily for Nordic enterprise clients. We deploy on regional infrastructure (Azure Sweden Central, AWS EU-north-1) using models with strong Swedish coverage (GPT-4o Realtime, Gemini Live) paired with ElevenLabs custom Swedish voices. Language detection and mid-call switching are handled in the orchestration layer so a caller can start in English and continue in Swedish without breaking flow.

A traditional IVR is a menu tree ("press 1 for sales") that captures roughly 60% of caller intent before mis-routing or hangup. An AI voice agent is a natural-language system that captures close to 100% of intent on the first turn, executes multi-step tasks (lookup, update, book), handles interruptions and clarifications, and only escalates when policy or complexity requires. It replaces the IVR, the routing rules and the tier-1 agent script in one layer.

A voice agent is scoped to the systems it has to touch, then built with an evaluation harness and a staged rollout. Managed operations begin once the agent is in production and continue as a monthly engagement with measures for latency, containment, CSAT and cost per call. We do not promise a go-live date before we have seen the workflow.

GPT-4o Realtime (OpenAI) currently leads on reasoning quality and multilingual coverage including Swedish, with sub-300ms voice-to-voice latency; billing is per audio minute. Amazon Nova Sonic (AWS) is optimised for enterprise deployment inside AWS accounts with native Amazon Connect integration, lower per-minute cost, and stronger data-residency terms for regulated workloads. Alice Labs selects per project: Nova Sonic when the client is AWS-committed and cost-sensitive at high volume, GPT Realtime when reasoning quality and language coverage dominate.

Ask whether the agency owns delivery end-to-end, can name clients, has an evaluation harness, and prices the work before it starts. Alice Labs is a global AI implementation consultancy with 100+ implementations and a 96% production rate, senior-only teams, and EU AI Act and GDPR alignment by default. The Ljusgårda order workflow is a named case. We fit mid-market and enterprise buyers who want the agent on their systems, not a platform to staff up around.