Practical AI implementation,
not hype.
Devlopa builds AI systems that work in production, from knowledge assistants and document pipelines to agent workflows and intelligent automation.
Book an AI ConsultationWhat we build
AI capabilities that ship.
Every capability below is production-tested, not theoretical. We design for reliability, explainability, and human oversight.
AI Strategy & Feasibility
We assess your use case, data, and constraints before recommending any architecture. Strategy first, technology second.
RAG & Semantic Search
Retrieval-Augmented Generation systems with document ingestion, semantic search, permission-aware retrieval, source citations, and evaluation frameworks.
Custom AI Agents
Autonomous agents with tool use, memory, planning, and orchestration, designed for specific business workflows, not general tasks.
Document Intelligence
Upload, OCR, classify, extract, and review pipelines with confidence scoring, human-in-the-loop review, and audit logging.
AI Workflow Automation
Replace manual processes with intelligent pipelines. Support triage, contract review, data extraction, report generation, and more.
Model Evaluation & Governance
Test sets, factual accuracy evaluation, hallucination monitoring, bias assessment, and governance frameworks for production AI systems.
AI Dashboards & Analytics
Admin panels showing usage patterns, failed queries, confidence distributions, and business-level outcomes from your AI systems.
Model Integration
OpenAI, Anthropic, Mistral, Llama, and local model integration into your existing products and workflows.
Representative case studies
Sample AI engagements.
The following projects are representative case studies based on real engagement patterns. Client types are used instead of named organizations.
Mid-sized Consulting Organization
Enterprise Knowledge Assistant
Problem: Internal documents scattered across Notion, Google Drive, PDFs, and CRM exports. Teams lost hours searching for prior work and technical notes.
Solution: Designed a secure RAG-based assistant with document ingestion, semantic search, permission-aware retrieval, response citation, and admin analytics.
Delivery phases
SaaS Support Team
AI Customer Support Workflow
Problem: Support agents handled repetitive onboarding and troubleshooting questions manually, creating high volume with low value.
Solution: Created an AI-assisted triage and response workflow with confidence thresholds, escalation rules, intent classification, and CRM integration.
Delivery phases
Legal Operations Team
Document Intelligence System
Problem: Manual document review was slow, inconsistent, and error-prone across large volumes of structured and unstructured documents.
Solution: Built a pipeline for document upload, OCR, classification, extraction, human review, and audit logging with confidence scoring.
Delivery phases
Ready to implement AI that actually works?
We start with a discovery session, understanding your use case, data, and constraints before recommending any architecture.