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Services / AI Agents & LLMs
Intelligent Agents

Deploy AI Agents That Think, Decide, and Act — Autonomously

We build custom AI agents powered by leading LLMs that handle customer queries, retrieve knowledge, summarize data, and execute multi-step tasks — 24/7, at scale, integrated with your existing systems.

80%
Query deflection rate
24/7
Always-on availability
<2s
Average response time
95%+
Answer accuracy (RAG)

Types of AI Agents We Build

Every agent is custom-built for your specific use case, trained on your data, and integrated with your tools — not an off-the-shelf chatbot.

Customer Service Agent

Handle tier-1 support tickets, FAQs, order inquiries, and escalation routing — trained on your product knowledge and policies.

Internal Knowledge Agent

Give employees instant access to company policies, procedures, and documentation through natural language queries — with accurate, cited answers from your knowledge base.

Data Analysis Agent

Ask questions about your data in plain English. The agent queries databases, runs calculations, and returns formatted summaries and insights without requiring SQL expertise.

Process Orchestration Agent

Multi-step agents that plan and execute complex tasks — calling APIs, making decisions based on results, and completing workflows that previously required human coordination.

Content Generation Agent

Generate brand-consistent content at scale — product descriptions, reports, proposals, and summaries — from structured data or conversational prompts.

Compliance Review Agent

Automatically review contracts, policies, and documents against your compliance rules — flagging issues, suggesting corrections, and maintaining audit logs of every review.

Our Technical Approach

We use Retrieval-Augmented Generation (RAG) and fine-tuning to make LLMs accurate and reliable on your specific data — not general-purpose tools prone to hallucination.

RAG Architecture

Your documents, databases, and knowledge bases are indexed as vector embeddings. The agent retrieves the most relevant context before generating each answer — grounding responses in facts, not guesses.

Model Selection

We select the right LLM (Claude, GPT-4, Gemini, or open-source models) based on your latency, cost, privacy, and accuracy requirements. No vendor lock-in.

Human-in-the-Loop

For sensitive decisions, we build escalation paths that route edge cases to human reviewers — maintaining control where it matters while maximizing automation everywhere else.

Frequently Asked Questions

How do you prevent AI agents from hallucinating wrong answers?+
We use RAG (Retrieval-Augmented Generation) which grounds every response in retrieved context from your knowledge base. Agents cite sources, and we configure fallback behaviors for low-confidence scenarios — defaulting to human escalation rather than a confident wrong answer.
Which LLM providers do you work with?+
We're provider-agnostic: Anthropic Claude, OpenAI GPT-4, Google Gemini, Mistral, and open-source models like Llama 3. We select based on your accuracy, latency, cost, and data privacy requirements.
How is our proprietary data kept secure?+
Your data never leaves your infrastructure unless you explicitly choose a cloud LLM API. We can deploy fully on-premise or in your own cloud account using self-hosted models. All data in transit and at rest is encrypted.
Can the agent access our internal tools and databases?+
Yes. We build tool-use capabilities into agents — connecting to your CRM, databases, APIs, and internal systems so the agent can both retrieve information and take actions on your behalf.
How long does it take to build a production-ready AI agent?+
A focused single-use-case agent typically takes 3–6 weeks from kickoff to production. More complex multi-agent systems with broad knowledge bases take 8–14 weeks. We deliver working prototypes early in the process.

Ready to Deploy Your First AI Agent?

Tell us the use case. We'll design an agent architecture, show you a prototype, and define the accuracy benchmark before any commitment.