contact@itechcloudsolution.com +91 997 9933 595 +91 972 6015 295
209-210-211, Western Plaza, Simada Naka, Surat, Gujarat, India 395006.
iTechCloud Solution
Book a call→
AI · Agent Development

Agents that do the work.
Safely, in your systems.

We design and build custom AI agents that plan, use your tools and APIs, and complete multi-step work, grounded in your data, governed by clear guardrails and evaluated before they go live.

Before · manual
✕Switch between five tools per request
✕Copy data between systems by hand
✕Wait in queues for simple answers
✕Follow up on every step manually
→
After · agent-assisted
✓Agent gathers context automatically
✓Updates systems through APIs
✓Resolves routine requests end to end
✓Escalates exceptions to a person
Custom
Built for your domain
Connected
Acts across your tools
Evaluated
Tested before launch
Governed
Guardrails & audit log
What is an AI agent?

More than a chatbot. Software that acts.

A chatbot answers questions. An agent works toward a goal: it decides which steps to take, calls tools and APIs, reads and writes data, and hands off to a person when it should. That makes it useful for real work, and it is why architecture and guardrails matter.

We build on Salesforce Agentforce where your work lives in Salesforce, and on custom frameworks where it does not, choosing the model and platform per use case.

Chatbot
Answers questions, then stops
Chatbot
Cannot act in your systems
AI agent
Plans steps and uses your tools
AI agent
Completes work, escalates exceptions
Why it matters

What agents change for your business.

Plain-English value: the outcomes teams actually feel.

Faster turnaround

Routine multi-step requests finished in minutes instead of queues.

Teams on higher-value work

People focus on judgment calls while agents handle the legwork.

Always available

Agents work outside office hours and across time zones.

Consistent and auditable

The same rules applied every time, with every action logged.

How it works

Four moving parts of a production agent.

STEP 01

Goal & instructions

A clear job, boundaries and success criteria the agent works toward.

STEP 02

Knowledge & memory

Grounding in your data and documents, plus context that carries across steps.

STEP 03

Tools & actions

APIs, Flows and functions the agent can call to read and change systems.

STEP 04

Guardrails & evaluation

Limits, approvals, hand-offs and tests that keep behaviour safe and reliable.

What agents handle

Where agents earn their keep.

Customer service

Resolve routine requests: order status, returns, account changes, with hand-off for the rest.

Sales & SDR work

Research accounts, qualify leads, draft outreach and book meetings.

Operations & finance

Process requests, check documents and update ERP and CRM records.

Internal help desk

Answer HR and IT questions and complete simple requests.

Research & reporting

Gather data from several systems and summarise it for decisions.

Humans in control

Autonomy with boundaries.

Every agent has clear limits: what it may do on its own, what needs approval and when to hand over to a person. We log every action so you can see and review what it did.

Approval gates
Sensitive actions wait for a person to approve.
Human hand-off
Clear rules for when the agent passes the conversation or task to a person.
Action log
Every tool call and decision recorded for review.
Scoped permissions
Agents only access the data and actions their job needs.
Engagement

From use case to agent in production.

01

Use case & design

Week 1

Pick the use case, define the goal, boundaries and success measures.

02

Data & tools

Weeks 2-3

Connect knowledge sources and build the actions the agent needs.

03

Build & iterate

Weeks 3-5

Prompting, orchestration and memory, reviewed with your team.

04

Evaluate & harden

Weeks 5-6

Test sets, edge cases, red-teaming and guardrail checks.

05

Deploy & monitor

Launch

Controlled rollout, monitoring and continuous improvement.

What we deliver

End-to-end agent delivery.

Agent Architecture

Single or multi-agent designs, orchestration and hand-offs chosen for the job.

Tool & API Integration

Secure connections to Salesforce, ERP, ticketing and internal APIs.

Memory & Context

Retrieval over your documents and data, plus conversation and task memory.

Guardrails & Evals

Evaluation suites, safety checks and limits tested before and after launch.

Agentforce Agents

Salesforce-native agents with topics, actions and the Einstein Trust Layer.

Monitoring & Tuning

Dashboards for quality, cost and usage, with ongoing improvement.

The stack Models, frameworks and platforms we build agents with.
Salesforce Agentforce OpenAI Anthropic Claude Google Gemini LangGraph LlamaIndex MuleSoft Salesforce Data Cloud Vector databases Python
Agents at work

Agent use cases, by industry.

Financial Services

Service & onboarding agents

Answer account questions and gather onboarding documents, with compliance hand-offs.

24/7 client support
Real Estate

Enquiry qualification

Qualify property enquiries, answer listing questions and book site visits.

Instant lead response
Healthcare

Scheduling & intake

Book, reschedule and prepare appointments with the right hand-offs to staff.

Fewer manual calls
Manufacturing

Order & supplier agents

Check order status, chase suppliers and update ERP records.

Faster order updates
Why iTech for AI agents

Agents that ship, not demos that stall.

Salesforce + AI in one team

Agentforce specialists and AI engineers who understand your CRM data.

Evaluation first

We measure quality with test sets before anything reaches users.

Safe by design

Guardrails, approvals and audit logs are part of every build.

Built for production

Monitoring, cost control and support after launch, not just a demo.

FAQ

AI agent development, answered.

A chatbot answers questions. An agent works toward a goal: it plans steps, uses tools and APIs, reads and updates data, and hands off to a person when needed.
If the work lives mainly in Salesforce, Agentforce is usually the fastest and best-governed option. For work across many other systems, or specialised models, a custom agent can fit better. We recommend per use case.
Scoped permissions, approval gates for sensitive actions, clear hand-off rules, evaluation before launch and a log of every action.
We choose per use case from providers such as OpenAI, Anthropic and Google, or models available through Salesforce, balancing quality, cost, latency and data residency.
A focused first agent typically takes around six weeks from use case to production, depending on data and integrations.
We design for providers and settings that do not train on your data, and keep sensitive data scoped to what the agent needs.

Put your first agent to work.

Book a free agent workshop. We will shortlist use cases, check your data and map a safe path to production.