01
Support operations
Ground answers in approved knowledge, complete safe actions and hand difficult moments to a person with context.
ServicesAI agent development
Production AI agents
AI Agent Development Company in India
ResoluteX builds AI agents that retrieve approved context, use narrowly defined tools, pause for human approval and leave an audit trail. The work starts with the operational decision the agent must support, not with a chatbot demo.
An agent that can be evaluated, observed and stopped before it can create operational risk.
Where this work fits
02
Document workflows
Classify, extract, compare and route documents while preserving sources and review checkpoints.
03
Revenue operations
Research accounts, prepare records and trigger approved CRM steps without giving the model unrestricted access.
04
Internal copilots
Answer policy and operational questions with permission-aware retrieval and cited evidence.
What you receive
- 01A tool and permission model for every action the agent can take
- 02Evaluation cases covering success, refusal and escalation
- 03Retrieval, model routing and cost controls where required
- 04Human approval and handoff paths for sensitive decisions
- 05Tracing, audit history, deployment assets and runbooks
How delivery works
- 01
Choose one bounded job
We start with a workflow where success, failure and escalation can be described clearly.
- 02
Design the control plane
Tools, permissions, data boundaries and approval points are defined before autonomous actions are enabled.
- 03
Build the evaluation set
Representative examples and failure cases become a regression suite for prompts, models and tools.
- 04
Release behind limits
The first production version ships with tracing, rate limits, fallbacks and a clear path to a person.
A good fit when
- The workflow has repeatable decisions and accessible source data
- A human already knows how to judge whether the result is acceptable
- The agent can begin with a narrow set of reversible actions
Probably not the right fit when
- There is no reliable source of truth for the agent to use
- The first release must make irreversible decisions without review
- The real problem is a missing workflow rather than an AI capability
Questions buyers ask
Before you scope the work
How much does an AI agent cost to build?
A focused first workflow usually fits a fixed sprint starting at $2.9k. Cost moves with the number of tools, data sources, approval paths, evaluation cases and production integrations.
Which AI models do you use?
The model follows the job. We can route between OpenAI, Anthropic, Google and other providers when capability, cost, residency or reliability requires it. The architecture avoids making one model a permanent dependency.
How do you prevent hallucinations and unsafe actions?
No single technique removes risk. We combine approved retrieval sources, constrained tools, structured outputs, evaluation suites, human approval, tracing and explicit refusal or escalation paths.
Can the agent run in our infrastructure?
Often, yes. The deployment boundary, model providers, secrets, retained traces and data access are agreed before the build starts.
Related services
Describe the outcome in one sentence. We will return a fixed sprint plan within one business day.
Scope a sprint