CAP_01
Agentic workflow systems
Multi-step agents that interpret goals, plan tasks, call approved tools, handle exceptions and return a useful result.
ORCHESTRATIONTOOL CALLING
Agentic AI engineering / Indian Mesh
We build the intelligence layer your business is missing.
AI models are powerful. Business context is what makes them useful. Indian Mesh engineers the layer between your business and AI—connecting your workflows, data, tools and people into systems your team can actually understand and operate.
Workflow-first engineeringHuman-in-the-loop controlsDesigned for integration
IM / ORCHESTRATIONSYSTEM READY
Business contextPolicies · SOPs · CRM · ERP · Team knowledge
INPUTIndian Mesh intelligence layerContext · Reasoning · Routing · Guardrails
CORESpecialist AI agentsRetrieve · Decide · Use tools · Escalate
AGENTSBusiness executionActions · Approvals · Audit trail · Outcomes
OUTPUTarchitecture.preview.json● human control enabled
Business-firstStart with the workflow, not the model.
Model-agnosticChoose technology to fit the use case.
Tool-connectedIntegrate with your existing stack.
Human-governedDefine when agents act or ask.
// 01 — The architecture
Not another chatbot.
A layer built for how you operate.
We translate the way your company works into a clear execution layer: what an agent needs to know, which tools it can use, what rules it must follow, and when your team should step in.
CONTEXT → ORCHESTRATION → EXECUTION
Every component has a defined role.
Every component has a defined role.
workflow.config● illustrative
// A business request becomes a governed workflow { "intent": "resolve_customer_request", "context": [ "company_policies", "customer_history" ], "tools": [ "crm.lookup", "ticket.update" ], "guardrails": { "approval_required": true, "log_actions": true }, "fallback": "human_handoff" }
Business context, not generic prompts
Ground workflows in the right documents, records, policies and definitions—with permissions that reflect your business.
Orchestration, not isolated agents
Coordinate the right models, tools and specialist agents around a task, rather than creating disconnected AI experiments.
Execution, not just suggestions
Connect to real systems and define which actions can run automatically, which need approval and which must be escalated.
Visibility at every step
Make the workflow understandable with logs, clear states, failure paths and feedback for continuous improvement.
// 02 — Engineering capabilities
From a single agent to an AI-enabled operation.
Composable services, engineered around your business logic and the systems you already use.
CAP_02
Enterprise knowledge & RAG
Retrieval and knowledge experiences that help teams get grounded answers from internal information and documents.
RAGKNOWLEDGE
CAP_03
Business system integration
Connect AI workflows with CRMs, ERPs, APIs, databases, websites and internal applications.
APICONNECTORS
CAP_04
Sales & customer operations
Assist with lead research, qualification, follow-ups, customer requests, ticket triage and service handoffs.
CRMSUPPORT
CAP_05
Document & data intelligence
Extract, validate, classify and route information from business documents and recurring data-heavy processes.
EXTRACTIONVALIDATION
CAP_06
AI governance & observability
Define access boundaries, approvals, evaluation, action logs, monitoring and safe fallbacks for production workflows.
EVALUATIONGUARDRAILS
// 03 — Delivery protocol
Engineered in stages.
Measured against real work.
We keep the scope concrete and the path collaborative—so the first deployment solves a defined problem and creates a foundation to build on.
Map the business logic
Document the workflow, users, data sources, bottlenecks, exceptions and measurable success criteria.
Define the agent system
Design context, tools, responsibilities, permissions, escalation paths and human approval points.
Integrate & evaluate
Build the workflow, connect systems and test against real examples, edge cases and failure scenarios.
Deploy & iterate
Monitor performance, gather team feedback and improve reliability as business needs evolve.
// 04 — Application layer
Where business workflows meet AI.
Potential starting points across the business. We prioritise use cases based on value, feasibility, risk and integration effort.
01 / Sales intelligence
Lead research, account briefs, CRM updates and follow-up preparation.
02 / Customer operations
Request classification, grounded answers, ticket updates and human escalation.
03 / Internal knowledge
Search company SOPs and policies, with answers linked to source material.
04 / Finance & admin
Document checks, data extraction, exception identification and approval routing.
05 / Operations & reporting
Collect information across systems and prepare structured operational summaries.
06 / Custom workflows
Connect the manual handoffs between teams, applications and business processes.
// 05 — Governance by design
Autonomy with boundaries.
Intelligence with accountability.
Agentic systems need more than a clever model. We design the operating rules around them, so your team knows what the system can access, what it has done and when it needs human judgment.
Least-privilege accessLimit data and tools to what each workflow needs.
Human approval gatesReview sensitive, irreversible or high-impact actions.
Traceable actionsCapture workflow steps and outcomes where appropriate.
Evaluation & fallbackTest known cases and route uncertainty to people.
// Start with a real problem
Bring us the workflow that shouldn't still be manual.
We’ll help map the process, identify where agentic AI fits and define a practical first build—with your team and existing systems in mind.