AI Agents for Business, With Clear Jobs and Clear Limits
An AI agent should have a defined task, approved information and permission to do only what that task requires. SolvTreeAI builds agents around business workflows, with human handoffs when the work needs judgement.
Mumbai-based. Serving businesses in India and the UAE.
A chatbot answers. An agent can take the next permitted step.
A chatbot may explain your services. An agent can also record an enquiry, retrieve an approved document or create a task in a business system, if it has the right integration and permissions.
That added ability creates responsibility. The agent needs a reliable source, bounded tools, an evaluation process and someone to handle the work it cannot complete.
We do not begin with an “autonomous employee” claim. We begin with one task your team can describe and check.
AI agent services and candidate workflows
Lead qualification and sales handoff
Ask approved questions, record the answers and route the enquiry to the right person. The agent should not invent a price, promise a delivery date or make a commercial commitment outside its authority.
Customer-request triage
Identify the type of request, retrieve approved information and collect what a person needs to resolve it. Complaints, sensitive issues and unclear requests need explicit escalation paths.
Internal assistants that can act
Find the relevant record, prepare a draft or create a task through an approved tool. A status answer should show its source. An action should leave a traceable record.
Voice and WhatsApp workflows
Where appropriate access and permissions exist, an agent can use voice or messaging for a bounded conversation. Calling eligibility, opt-outs, consent, retention and human handoff must be addressed for the market and use case.
An agent does not automatically need every channel. Choose the one that fits the task and can be operated responsibly.
What every agent needs before release
| Component | Question to answer |
|---|---|
| Task | What exact outcome is the agent responsible for? |
| Knowledge | Which source is authoritative, and how is it updated? |
| Tools | Which records can it read, create or change? |
| Permissions | Which actions require approval or are blocked entirely? |
| Handoff | Who receives the case, and what context is included? |
| Evaluation | Which normal and difficult cases must it pass? |
| Operation | Who reviews failures and changes the workflow? |
These controls matter more than whether a conversation sounds human. A confident wrong answer can be worse than a clear handoff.
Our build process
Define the task and the refusal boundary
Agree what a completed task looks like, what information may be used and when the agent must stop. Keep the first scope narrow enough to evaluate.
Connect approved knowledge and tools
Use the necessary data rather than every available record. Define what happens when sources disagree, information is stale or an integration is unavailable.
Test the real failure cases
Include missing information, ambiguous requests, attempted instructions that conflict with the workflow and repeated tool calls. Check that private information stays within the agreed scope.
Release with a human operator
Start with suitable review controls. Agree how conversations or actions are inspected, how the agent is paused and who handles escalated cases. Ongoing operation is part of the system, not an optional afterthought.
Where a business agent may fit
- Freight/logistics: collect shipment details and prepare the next task for an operator.
- Real estate: qualify enquiries and route them without inventing availability or terms.
- Contracting: gather site updates and flag missing information for review.
- Distribution: retrieve approved stock or order information and prepare a follow-up.
- Hospitality: route guest enquiries or run an agreed guest-contact workflow.
- Travel: collect itinerary preferences and pass booking decisions to an operator.
These are possible scopes, not guarantees of a finished product for every industry or channel.
Inspect the difference between built work and a design
Our hotel voice re-engagement project describes a voice workflow for an Indian hotel. It is a market-specific example, not a claim that the same calling or data rules apply in the UAE.
The lead-qualification concept is described as designed. Its desired conversion figures are targets, not verified achieved results. Client names are withheld and public dashboards use sample data.
Engagement and pricing
Agent scope depends on channels, knowledge sources, integrations, permitted actions and the evaluation effort. Model usage, telephony, messaging, hosting and monitoring can create recurring charges.
Agree the build scope, operating responsibilities and usage assumptions separately. A voice agent with business-system access is not priced or supported like a simple website FAQ bot.
We will not promise that a custom agent can replace a role before the workflow has been tested and the operating cost is understood.
Frequently asked questions
What are AI agents for business?
They are software systems that interpret a request and use approved knowledge or tools to complete a defined task. A business agent needs limits, monitoring and a human route for work it cannot safely complete.
How is an AI agent different from a chatbot?
The distinction is what the system can do. A chatbot may only respond with text. An agent can also perform permitted actions through connected tools. Product labels overlap, so inspect the actual workflow and permissions.
Can an AI agent use our CRM or ERP?
It may be able to if approved integration access exists. Define the records it may read or change, the validation rules and which actions need approval. Do not give it broad access simply because an API is available.
Can it make calls or use WhatsApp?
Potentially, with appropriate platform access and an approved use case. Calling, consent, opt-out, data and messaging requirements must be assessed for the relevant market. This page makes no blanket compliance promise.
What happens if the agent does not know the answer?
It should acknowledge the limit, avoid inventing an answer and hand off with the relevant context. The destination and response owner must be agreed before release.
How do you measure whether an agent is useful?
Use task-specific checks such as correct completion, escalation quality, unsupported answers, handling effort and usage cost. Review representative cases and outcomes; conversation volume by itself is not a success measure.
Give the agent a job your team can verify
Start with a task, a source of truth and a person who owns the exceptions. We can help scope the smallest useful agent around that work.