Automate workflows
Assist with classification, retrieval, extraction and structured processing.
Custom AI Agent Development | Intelligent Business Automation
AI agents built to understand, act and deliver.
Transform the way your business works with custom AI agents that automate workflows, use business knowledge, connect with your software and support smarter decisions.
We combine LLMs, RAG, APIs, automation workflows and secure integrations around your processes—not a generic chatbot template.
- Custom AI agents
- RAG & knowledge
- Workflow automation
- Multi-agent systems
- CRM / ERP integration
AI AgentReason · Retrieve · Act
- 11
- Years experience
- 1,500+
- Projects delivered
- 700+
- Clients served
- 16+
- Industries served
01What is AI agent development?
Software that can reason, use tools and execute defined tasks.
An AI agent interprets a request, works with relevant information, selects approved tools and performs steps toward a specific objective. Unlike a basic chatbot, it can retrieve records, call APIs, update supported systems and coordinate controlled workflows.
We use AI only where it adds value—combining flexible interpretation with reliable software logic, permissions, monitoring and human review.
- UnderstandInterpret intent and context
- RetrieveFind approved information
- ActUse tools within limits
- VerifyLog, review and improve
Move beyond repetitive work with intelligent automation.
Improve response
Answer common questions and route complex requests to the right team.
Connect systems
Use approved APIs to retrieve information and initiate permitted actions.
Unlock knowledge
Search business documents, databases and internal resources naturally.
Support sales
Qualify enquiries, update CRM records and recommend follow-up actions.
Improve visibility
Log outcomes, surface exceptions and identify where humans should intervene.
03AI agent services
Custom agents designed around your business.
Start focused, validate the workflow and scale only where the evidence supports it.
Custom AI Agent Development
Architecture, model selection, tools, business rules, context, testing and monitoring for a specific objective.
AI Workflow Automation
AI reasoning combined with deterministic rules, API calls, approvals and cross-application workflows.
Customer Support Agents
Grounded answers, knowledge search, status lookup, ticket creation, analytics and human escalation.
Sales & Lead Agents
Capture, qualify and route enquiries while keeping CRM and follow-up workflows organised.
RAG Knowledge Agents
Source-aware assistance using approved documents, metadata, vector search and access controls.
Research & Analysis Agents
Collect approved information, compare documents, explore patterns and prepare human-reviewed reports.
Multi-Agent Systems
Specialised roles, orchestration, controlled handoffs, shared context and validation for complex tasks.
ERP, CRM & SaaS Agents
Natural-language access, record lookup, task creation and role-aware actions inside business software.
Document Processing
Classification, extraction, comparison, validation and exception handling for document-heavy operations.
Voice AI Agents
Speech workflows, structured data collection, call summaries, handoff and consent-aware processing.
SaaS & Product Agents
In-app assistants, natural-language search, contextual help, reports and tool-using product features.
Consulting, MVP & PoC
Feasibility, data readiness, prototype development, evaluation criteria and a production roadmap.
Not every problem needs the most complex AI.
- Predictable
Rule-based chatbot
Fixed questions, predefined flows and predictable interactions.
- Flexible
Conversational assistant
Understands natural language and answers without necessarily taking action.
- Tool-using
AI agent
Retrieves information, selects tools and completes approved multi-step tasks.
- Orchestrated
Multi-agent system
Coordinates specialised roles when controlled collaboration provides real value.
05Production-oriented stack
Modern technology, selected for the use case.
We evaluate model quality, privacy, latency, integrations, maintenance and cost before choosing the final stack.
Models
- OpenAI
- Anthropic
- Gemini
- Open-weight
Agent systems
- LangChain
- LangGraph
- LlamaIndex
- Custom logic
Engineering
- Python
- FastAPI
- Node.js
- Next.js
Data & retrieval
- PostgreSQL
- MongoDB
- Redis
- Vector search
Deployment
- AWS
- Docker
- Linux
- CI/CD
Integration
- REST APIs
- Webhooks
- OAuth
- Event workflows
06Security, governance & reliability
Clear permissions. Human control. Operational visibility.
An agent that can access data or execute actions needs more than a good prompt. We define exactly what it can see, what it can do and when a person must approve.
- Access controlLeast-privilege tools and records
- Human approvalReview sensitive or irreversible actions
- Prompt safeguardsReduce manipulation from untrusted inputs
- Audit logsRecord calls, approvals, errors and outcomes
- EvaluationTest edge cases and failure scenarios
- MonitoringTrack quality, latency, usage and cost
Action requires approvalRefund over limit · routed to a person
From business problem to a tested AI solution.
- 01
Discovery
Define tasks, challenges and measurable outcomes.
- 02
Feasibility
Assess models, APIs, data and limitations.
- 03
Data planning
Map sources, permissions and integrations.
- 04
Prototype
Validate the workflow with a focused PoC.
- 05
Development
Build prompts, tools, retrieval and validation.
- 06
Evaluation
Test quality, security, latency and cost.
- 07
Deployment
Connect the solution to supported systems.
- 08
Improvement
Monitor outcomes and update responsibly.
Intelligent automation across operations.
eCommerce & Retail
Product discovery, order support and enquiry classification.
Healthcare
Administrative assistance, approved knowledge and appointment workflows.
Education
Admission routing, resource search and student information.
Real Estate
Property search, enquiry qualification and appointment coordination.
Finance
Document extraction, report preparation and policy search with oversight.
Manufacturing
SOP knowledge, inventory information and exception reporting.
IT & Software
Documentation search, ticket classification and developer assistance.
SaaS Products
In-app assistants, workflow automation and product-specific AI features.
09Implementation scope
Start at the right level for your business.
Final cost depends on workflow complexity, integrations, model usage, data readiness, security and expected volume.
- Validate
AI Agent Proof of Concept
One defined use case, limited data or tools and initial evaluation.
- Automate
Single-Workflow Agent
Agent logic, API integration, business rules, validation and deployment.
- Integrate
Business AI Agent
Multiple systems, structured execution, role access, logging and monitoring.
- Orchestrate
Advanced Multi-Agent
Specialised roles, coordination, evaluation, security and production planning.
AI + software engineering10Why Shineing Digital LLP?
A technology partner for practical AI innovation.
We connect AI capability with software engineering, business workflows and measurable outcomes.
- Business-first architectureAI, conventional automation or both—based on the task.
- Custom-built solutionsWorkflows designed around your systems and constraints.
- Controlled executionPermissions, validation and approvals matched to risk.
- Transparent scopeFunctionality, dependencies and limitations defined early.
- Scalable deliveryStart with a focused PoC and expand after evaluation.
- Ongoing improvementMonitoring and maintenance as models and needs evolve.
Practical answers before you invest.
Still evaluating a use case? Start with a technical consultation.
Book a technical consultationWhat is an AI agent?
An AI agent is software designed to understand requests, retrieve relevant information, use approved tools and complete defined tasks within permissions and safeguards.
How is an AI agent different from a chatbot?
A chatbot primarily responds. An agent can also retrieve records, call APIs and perform approved multi-step actions.
Can you integrate with our existing software?
Yes, where suitable APIs, database access and permissions are available. Scope depends on each system’s technical capabilities.
Do we need a multi-agent system?
Usually not at first. We recommend multiple agents only when specialised roles and controlled handoffs clearly improve the workflow.
How do you reduce unsupported answers?
We use grounding, RAG, source controls, validation, evaluations and escalation paths. These reduce risk but cannot guarantee every AI output is correct.
Can we begin with a proof of concept?
Yes. A focused PoC is often the best way to test feasibility, quality, latency and likely operating cost before production investment.
12Build with clarity
Turn one high-value workflow into your first reliable AI agent.
We’ll help define the task, validate the approach and build the right level of intelligence and control.
Let’s build an AI agent for your business.Tell us what you want to automate. We’ll assess feasibility, suitable technologies and a practical development approach.
- Use-case and workflow assessment
- Integration and data-readiness review
- Architecture, timeline and scope guidance