Function & Tool Calling Agents
Agents capable of taking actions in your live systems: querying customer records, updating inventory statuses, booking appointments, and triggering notifications via webhooks.
Intelligent Systems
AI Agent & Workflow Automation Services
Transform operational bottlenecks with intelligent AI agents that execute real tasks: automated data extraction, document processing, multi-step LLM workflows, and tool calling connected directly to your production APIs.
Direct Answer
What are AI agent and workflow automation services?
AI agent and workflow automation services involve developing autonomous software agents that utilize Large Language Models (LLMs) and deterministic function calling to automate multi-step operational tasks. Acelizum Technologies builds custom AI workflows that parse documents, query internal databases, trigger background jobs, and integrate seamlessly with production APIs.
Deterministic Execution
Secure Private Embeddings
Claude 3.5 & GPT-4o Integration
Local LLM Deployments
AI Capabilities
Practical artificial intelligence built for tangible business ROI
We do not build generic chatbots that hallucinate answers. We engineer deterministic agentic systems designed to eliminate repetitive manual hours across your operational workflows.
Document Parsing & OCR Pipelines
Automate extraction of unstructured invoices, PDFs, flight tickets, and receipts into validated JSON data structures stored directly in PostgreSQL or MySQL.
Multi-Model Orchestration
Combine the reasoning power of Anthropic Claude 3.5 Sonnet, OpenAI GPT-4o, and cost-effective local open-source models via Ollama to balance latency, accuracy, and operational cost.
Internal Knowledge Retrieval (RAG)
Vector embeddings and semantic search across company handbooks, support tickets, and codebases using pgvector or Redis for hallucination-free organizational intelligence.
Human-in-the-Loop Oversight
Built-in administrative approval gates for high-stakes actions like payment dispatches or contractual drafts, ensuring complete accountability and compliance.
Latency & Token Budget Optimization
Carefully engineered system prompts, prompt caching, response streaming, and structured schema outputs that cut LLM API bills by up to 70%.
Engineering Safety
Security, privacy, and non-hallucinating agent design
Connecting AI to internal databases requires rigorous safety bounds. We enforce strict JSON schemas on every LLM output, sanitize all tool parameters before SQL execution, and sandbox agent permissions.
Read about our full-stack architecture and engineering team on our about page or see our live systems in the portfolio.
Schema validation on 100% of LLM tool call payloads.
Zero data training: client data is never used to train public foundation models.
Comprehensive audit logs tracking every prompt, tool call, and state transition.
Graceful fallbacks ensuring systems continue functioning if an AI API errors.
AI FAQ
Frequently asked questions about our AI workflow solutions
How do you prevent AI hallucinations in business software?
We use structured function calling with Pydantic or JSON schema validation, ground agent prompts with exact database lookups (RAG), and enforce deterministic logic boundaries where the model is only permitted to select pre-authorized actions.
Can AI agents run on our private servers for data privacy?
Yes. We can deploy private, open-source models (such as Llama 3, Mistral, or DeepSeek) within your own VPC or on-premise Docker infrastructure using Ollama or vLLM, ensuring zero data leaves your network.
How long does it take to implement a production AI workflow?
A focused document parsing or tool-calling workflow typically ships within 2 to 4 weeks. Enterprise multi-agent automation systems usually take 6 to 10 weeks with thorough staging tests.
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