IMPETIC
ai & automation

AI & Automation Services

Embedding real intelligence into your product — not a chatbot bolted on, a system built for it.

Most “AI features” are surface-level; Impetic builds AI as core infrastructure — retrieval, memory, evaluation, and guardrails included from day one, not bolted on after launch.

What We Build

Engineered for Intelligence

Production-grade artificial intelligence systems designed to scale.

LLM & Chatbot Integration

Production-grade conversational interfaces wired into your real data and workflows.

LLM APIWorkflowsReal-Time Data

Retrieval-Augmented Generation (RAG)

Grounding model outputs in your own documents, product data, and knowledge base.

RAGVector DBSemantic Indexing

Custom AI Agents

Multi-step autonomous workflows that take real actions, not just generate text.

Autonomous AgentsTool CallingMulti-Step Execution

Workflow & Process Automation

Replacing manual, repetitive operations with reliable automated pipelines.

Process AutomationETL PipelinesSLA Guarantees

Predictive Analytics & ML Models

Forecasting, scoring, and classification models trained on your proprietary data.

Predictive MLScoring ModelsClassification

AI-Powered Search & Recommendations

Semantic search and personalization that actually understands user intent.

Semantic SearchEmbeddingsPersonalization

Model Fine-Tuning & Evaluation

Tailoring and rigorously testing models against real-world edge cases.

Fine-TuningEval BenchmarksEdge-Case Guardrails

MLOps & Model Deployment

Versioning, monitoring, and safely rolling out model updates in production.

MLOpsModel MonitoringCI/CD Pipelines
Integration Path

AI Engineering Process

A systematic roadmap from initial audit to production telemetry.

Step 01

Audit

Map where AI creates real leverage in your product and identify high-impact integration points.

Step 02

Prototype

Build a working proof of concept fast to validate accuracy, response time, and user experience.

Step 03

Integrate

Wire model pipelines into production data, authentication systems, and scalable cloud infrastructure.

Step 04

Monitor

Evaluate output quality, monitor token latency, retrain models, and improve performance continuously.

AI Frameworks & Infrastructure Tools
OpenAIAnthropicLangChainPineconeHugging FacePyTorchLlamaIndexWeights & Biases
Get Started

Have an AI idea that needs real engineering behind it?

Discuss your AI product strategy with our lead AI infrastructure architects.