Custom AI Development
Built for Real Enterprise ROI.
Move beyond generic chatbot wrappers. We architect production-grade LLM applications, private RAG knowledge hubs, and autonomous operational agents that integrate securely with your internal databases and business software.
Production AI Capabilities Engineered for High-Value Operations
We design and deliver robust AI systems that solve genuine business problems without hallucinations or fragile prompt engineering.
Enterprise RAG & Search
Connect millions of PDFs, manuals, legal contracts, and ticket histories into a semantic retrieval engine with verbatim source citations.
Autonomous Sales & Triage Agents
Multi-lingual agents that converse over WhatsApp and web, qualify buyer requirements, check real-time inventory, and schedule calendar appointments.
Intelligent Document Extraction
Parse complex invoices, bank statements, purchase orders, and medical reports into structured JSON tables validated directly against ERP ledgers.
Private On-Premise LLMs
Deploy quantized Llama 3, Mistral, or DeepSeek models on local GPU servers or private isolated cloud containers for complete regulatory compliance.
Multi-Agent Workflow Orchestration
Coordinate specialized sub-agents: Researcher, Critic, Database Query Writer, and Formatter to solve complex multi-step analysis tasks automatically.
Automated Fine-Tuning Pipelines
Curate domain datasets and fine-tune specialized models for clinical jargon, Indian legal phrasing, or proprietary internal nomenclature.
Enterprise Security & Privacy Architecture
Most enterprise leaders hesitate to adopt AI due to concerns over confidentiality and intellectual property loss. We construct defensive multi-tier architectures where your data never trains public foundation models.
Verified Technology Partners
Transparent AI Project Pricing
Fixed milestone scopes designed for quick validation and scalable production rollout.
AI Copilot / Agent
Single-task intelligent assistant for customer support triage, WhatsApp brochure dispatch, or lead qualification.
- ✓ Single-channel integration (WhatsApp or Web)
- ✓ Grounded knowledge base (up to 200 documents)
- ✓ Lead qualification & CRM webhook sync
- ✓ Latency-optimized prompt engineering
- ✓ Timeline: 2–3 weeks
Enterprise RAG Engine
Complete internal company brain querying thousands of unstructured PDFs, policies, tickets, and internal database rows.
- ✓ Hybrid vector + keyword search pipeline
- ✓ Multi-document OCR & tabular data parsing
- ✓ Exact page/paragraph source attribution
- ✓ Role-based access control & token security
- ✓ Admin evaluation dashboard with latency metrics
- ✓ Timeline: 4–6 weeks
Autonomous System
Multi-agent architecture that plans, executes database writes, triggers external APIs, and generates complex analytical reports.
- ✓ Multi-agent tool execution & loop guardrails
- ✓ Private VPC / On-premise GPU model hosting
- ✓ Automated model fine-tuning & evaluation loops
- ✓ Bi-directional ERP / CRM synchronization
- ✓ SLA support & continuous prompt optimization
Frequently Asked Questions About Custom AI Development
Practical insights on costs, model selections, hallucination mitigation, and deployment.
How does Johnson Softwares prevent hallucinations in enterprise AI systems?
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We engineer deterministic Retrieval-Augmented Generation (RAG) architectures with multi-stage verification layers. We combine hybrid vector search (dense embeddings + sparse BM25 indexing) with semantic re-ranking, strict temperature controls, and citation metadata. If information is absent from your approved source data, the AI safely triggers fallback protocols rather than guessing.
Is our proprietary company data used to train public LLM models?
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Never. We enforce strict enterprise zero-data-retention agreements when integrating cloud LLMs (such as Azure OpenAI, Anthropic Claude, or Google Vertex AI). For healthcare, legal, or financial entities with rigorous compliance rules, we deploy open-weights models (like Llama 3 or Mistral) inside your isolated private VPC or on-premise GPU clusters with zero external network connectivity.
What is the difference between an AI chatbot and an autonomous AI agent?
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A chatbot merely responds to conversational prompts. An autonomous AI agent possesses tool-calling capabilities: it can parse an incoming inquiry, query your PostgreSQL database, generate a PDF quotation, trigger an email or WhatsApp alert, and update your CRM stages autonomously without human intervention.
What tech stack do you use for custom AI development?
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Our core AI engineering stack utilizes Python (FastAPI), LangChain/LlamaIndex, PostgreSQL with the pgvector extension, Redis for context window state caching, and high-performance React/Next.js interfaces for human-in-the-loop audit consoles.
How long does it take to deploy an enterprise AI application?
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A focused RAG knowledge assistant or document extraction pipeline typically deploys to staging within 3 to 4 weeks. Multi-agent operational systems with database write permissions take 6 to 10 weeks, backed by comprehensive automated test suites.
Ready to Deploy Production AI in Your Business?
Speak with our senior AI solutions engineer. We will review your data pipelines, determine the optimal model architecture, and outline a fixed milestone roadmap.