Digital Transformation · Agentic AI & Intelligent Automation

Digital Transformation Services
AI Agents. Smarter Engineering.

Domain-Specific AI Chat Agents for Automotive Engineering & Enterprise Operations

IAST builds production-grade AI agent solutions that bring conversational intelligence to complex engineering domains and enterprise workflows. From AUTOSAR configuration assistants to company-wide policy knowledge bases, our agents are grounded in your proprietary data, built for accuracy, and designed for real-world engineering environments.

AUTOSAR Agent Company Policy Agent RAG Architecture LLM Integration Agentic AI Enterprise Knowledge Base Automotive AI
Intelligent Agents Built by IAST

Two production-proven AI chat agents — each purpose-built for a specific domain, powered by Retrieval-Augmented Generation (RAG), and grounded in your organisation's own documentation and standards.

01 — AUTOSAR AGENT

AUTOSAR Engineering Agent

A domain-specific conversational AI agent that gives automotive software engineers instant, accurate answers from AUTOSAR specifications, SWS documents, and ARXML schemas. Engineers can ask complex configuration questions, get guided walkthroughs of AUTOSAR modules, and receive cited, verifiable responses — all without leaving their development environment.

AUTOSAR SWS RAG ARXML Awareness Cited Answers Configuration Q&A ISO 26262 Context Hybrid Search
02 — COMPANY POLICY AGENT

Company Policy & Knowledge Agent

An enterprise-wide AI assistant that gives employees instant, natural-language access to internal HR policies, compliance guidelines, operational procedures, and company standards. Backed by RAG over your internal document corpus, it delivers consistent, accurate guidance at scale — reducing policy query load on HR and compliance teams while improving staff confidence and adherence.

HR Policy Q&A Compliance Guidance Onboarding Automation RAG over Internal Docs Role-Based Access Audit-Ready Citations
What the AUTOSAR Agent Can Do

Built to handle the depth and precision required by automotive embedded engineers — from day-to-day configuration questions to complex cross-module dependency queries across AUTOSAR Classic and Adaptive specifications.

01 — SPECIFICATION Q&A

AUTOSAR Specification Q&A

  • Instant answers from AUTOSAR Classic & Adaptive SWS documents
  • Section-level citations so engineers can verify every response
  • Cross-module queries spanning BSW, RTE, and application layers
  • Version-aware retrieval (AUTOSAR R19, R20, R21, R22+)
  • Natural language to technical specification bridging
02 — ARXML & CONFIGURATION

ARXML Configuration Assistance

  • Guidance on ARXML element structure and valid configurations
  • Module configuration walkthroughs (Com, Os, Mem, Diag, etc.)
  • Inter-component dependency explanations and validation hints
  • Error interpretation for ARXML schema violations
  • Best-practice recommendations for ECU platform configurations
03 — COMPLIANCE & SAFETY CONTEXT

Safety & Compliance Awareness

  • ISO 26262 requirement traceability context within AUTOSAR
  • ASIL decomposition guidance across software components
  • Safety-relevant BSW module configuration checks
  • SOTIF and cybersecurity (ISO 21434) alignment queries
  • Compliance gap identification in configuration documentation
04 — DEVELOPER PRODUCTIVITY

Engineering Workflow Acceleration

  • Inline IDE integration (VS Code, Eclipse-based tools)
  • Boilerplate code and configuration template suggestions
  • Onboarding support for engineers new to AUTOSAR projects
  • Reduction in context-switching between tools and manuals
  • Consistent, versioned knowledge base across distributed teams

Hallucination Control & Engineering-Grade Accuracy

Every answer from the AUTOSAR Agent is grounded in retrieved document chunks with section-level citations. An LLM-as-a-Judge validation layer cross-checks generated responses against retrieved evidence — ensuring the precision required for safety-critical embedded software development.

What the Policy Agent Can Do

An enterprise knowledge assistant that turns static policy documents into a live, conversational interface — making compliance, HR guidance, and operational knowledge instantly accessible to every employee.

01 — POLICY Q&A

Interactive Policy Assistant

  • Natural-language Q&A over HR policies, SOPs, and manuals
  • Instant answers for leave, benefits, code of conduct, and expenses
  • Source-cited responses referencing the exact policy document and section
  • Multi-language support for global teams
  • Always in sync with the latest published policy versions
02 — COMPLIANCE & GOVERNANCE

Compliance & Risk Support

  • Guidance on regulatory obligations (GDPR, POSH, labour law)
  • Automated policy acknowledgement and attestation workflows
  • Proactive flagging of policy-relevant situations
  • Audit-ready interaction logs for compliance reporting
  • Role-based access control for sensitive policy tiers
03 — ONBOARDING & HR AUTOMATION

Onboarding & HR Lifecycle

  • Guided onboarding journeys for new joiners
  • Policy training delivery and comprehension Q&A
  • Automated document checklist and submission tracking
  • Reduction in HR ticket volume for common policy queries
  • Scalable to thousands of concurrent users across geographies
04 — KNOWLEDGE MANAGEMENT

Centralised Knowledge Access

  • Single interface across disparate internal knowledge sources
  • Continuous document ingestion as policies are updated
  • Usage analytics to identify knowledge gaps in documentation
  • Integration with HRMS, Slack, MS Teams, and intranet portals
  • Feedback loops for ongoing response quality improvement

Scalable, Consistent Policy Guidance at Global Scale

Unlike email or helpdesk-based policy support, the Company Policy Agent handles thousands of concurrent queries with no wait time — delivering consistent, accurate, and up-to-date guidance regardless of time zone, department, or employee tenure.

How We Build Production AI Agents

Our AI agent delivery process combines domain expertise, rigorous RAG engineering, and iterative validation — producing agents that are accurate, reliable, and ready for real-world production use from day one.

1

Domain Discovery & Data Audit

Identify the knowledge corpus (specifications, policy documents, SOPs), assess document quality, define query types, and establish accuracy KPIs for the agent.

2

Data Ingestion & Chunking

Apply domain-aware parsing and semantic chunking strategies — preserving hierarchical structure in technical documents like AUTOSAR SWS or policy manuals — and index into the vector store.

3

RAG Pipeline Engineering

Build a hybrid retrieval pipeline (vector + keyword search), implement metadata filtering, and configure re-ranking to maximise retrieval precision for domain-specific terminology.

4

LLM Integration & Prompt Engineering

Select and configure the appropriate LLM (cloud or on-premise), engineer system prompts for domain grounding, and implement citation generation and hallucination control layers.

5

Evaluation & Red-Teaming

Measure retrieval precision, faithfulness, and answer relevance against domain-specific test suites. Conduct adversarial testing to ensure robustness against edge-case and out-of-scope queries.

6

Deployment & Continuous Improvement

Deploy via web chat, IDE plugin, or enterprise messaging integration. Monitor interaction quality, refresh the knowledge corpus, and refine the pipeline as documents evolve.

Why Choose IAST for Digital Transformation

Four core engineering strengths that make IAST the right partner for digital software modernization, AI agent intelligence, and enterprise transformation.

01

AI/ML Intelligence & Agentic AI

Engineering domain-tuned AI intelligence, agentic workflow automation, and RAG systems that reason over enterprise software, legacy codebases, and complex business workflows.

02

Intelligent Process Automation & Insights

Replacing manual engineering tasks with automated multi-agent orchestration, root-cause analysis engines, predictive insights, and executive decision-support dashboards.

03

Enterprise Security & Data Privacy

Deployable in air-gapped, on-premise, or private cloud environments with OAuth2/RBAC, KMS data encryption, strict identity management, and audit-ready data governance.

04

Modern Architecture & Legacy Refactoring

Modernizing legacy monoliths into cloud-native microservices, multi-tenant digital platforms, REST/SOAP middleware, and responsive multi-channel applications (desktop/browser/mobile).

Tools & Platforms We Work With

We leverage industry-leading LLMs, vector databases, RAG frameworks, and enterprise integration platforms to build robust, production-hardened AI agent solutions.

Large Language Models

OpenAI GPT-4o, Anthropic Claude, Google Gemini, and locally hosted open-source models (Llama 3, Mistral, Phi-3) via Ollama for private deployments.

RAG & Retrieval Frameworks

LangChain, LangGraph, LlamaIndex — with hybrid retrieval (vector + BM25), re-ranking, and metadata-filtered semantic search for high-precision document retrieval.

Vector Databases

Chroma, Pinecone, Weaviate, and pgvector — selected based on data scale, latency requirements, and whether the deployment is cloud-hosted or on-premise.

Document Processing

Advanced PDF/ARXML parsers, semantic and structural chunking pipelines, OCR for scanned documents, and automated re-indexing when source documents are updated.

Integration & Deployment

VS Code extensions, Eclipse plugin integration, Slack and MS Teams bots, REST API interfaces, and Docker/Kubernetes for scalable enterprise deployments.

Evaluation & Monitoring

RAGAS evaluation framework, LangSmith tracing, custom domain-specific test suites, and real-time monitoring dashboards for retrieval quality and response faithfulness.

Measurable Outcomes from IAST AI Agents

Domain-specific AI agents deliver immediate, measurable improvements in engineering productivity, compliance confidence, and operational efficiency — from the first week of deployment.

Faster Engineering Decisions
Reduced Manual Spec Lookup Time
Improved Compliance Adherence
Lower HR Query Volume
Engineering Productivity Gains
Consistent, Auditable Responses
Faster Onboarding for New Engineers
Secure, Private Data Handling

From Spec Lookup to Strategic Engineering

Engineering teams using domain AI agents consistently report 10–20% reductions in time spent on specification navigation and documentation queries — freeing engineers to focus on design, validation, and innovation rather than manual information retrieval.

Ready to Deploy an AI Agent for Your Engineering Team?

Partner with IAST to build domain-specific AI agents — grounded in your own documentation, engineered with automotive-grade accuracy, and deployed securely within your infrastructure.