Enterprise-Grade Autonomous AI Agents for Any User,
for Scalable Automation
Our automation framework is built to design, deploy, and orchestrate autonomous AI agents capable of performing context-aware tasks across enterprise environments. Unlike traditional rule-based systems, Agentic AI leverages State-of-the-Art foundation models, domain-specific adapters, and real-time multi-source data integrations to deliver intelligent task execution with minimal human oversight.
Built on top of LLMs, API orchestration layers, and secure knowledge retrieval mechanisms, Agentic AI agents are capable of dynamic decision-making, multi-step planning, and interfacing seamlessly with enterprise-grade software stacks.
Custom Autonomous Agents Tailored to Your Workflows
The Build New Agent module provides a configurable environment for constructing domain-specific AI agents using declarative workflows, prompt engineering, and API integrations. These agents can:
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Interface with structured and unstructured data via RAG (Retrieval-Augmented Generation)
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Execute multi-modal tasks with branching logic and memory persistence
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Integrate securely with internal systems via RESTful APIs, SQL databases, and SaaS platforms
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Automate decision loops with configurable confidence thresholds and fallback routines
Use cases
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Financial modelling agents
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Compliance and audit report generators
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Technical support triage bots
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Sales intelligence agents
This module enables technical teams to deploy agents across verticals like finance, operations, legal, and compliance with full observability and auditability.
Build once. Evolve continuously. Deploy anywhere.
Customized workflow builder chaining multiple agents, data sources and tools
The build workflow feature helps to build multi-agent workflow which makes handling non-linear tasks much efficient without human intervention. This feature allows the user to:
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Build workflows with existing agents.
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Configure data sources and tools for each agent.
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Setup automatic prompt tuning based on the agent’s role and task
This module eases technical and non-technical team’s workflow in building a deployable multi-agent pipeline.
Intelligent Talent Acquisition at Scale
The Recruitment Fleet automates and augments the hiring lifecycle using a multi –agent approach on recruitment workflows, where the tasks are distributed among the agents.
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Parses resumes and vector-based candidate-job profile matching
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Autonomous pre-screening via conversational interfaces
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Priority ranking based on skill fit, experience, and inferred intent
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Integration with Applicant Tracking Systems (ATS) and calendar tools
This enables HR teams to scale sourcing efforts, reduce manual evaluation workloads, and enhance candidate engagement with minimal configuration overhead.
Transform recruiting from reactive to predictive.
AI-Powered Internal Employee Services
The HR Fleet functions as an always-available virtual HR assistant, designed to streamline internal operations and reduce dependency on human HR personnel. It supports:
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Natural language queries for HR policies, payroll, and leave balance. Employees get instant, policy-compliant responses on leave, payroll, and benefits.
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Guided workflows for onboarding, appraisal cycles, and asset requests.
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Feedback and sentiment analysis through embedded pulse surveys.
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Integration with enterprise HRMS platforms and internal knowledge bases.
The HR Agent is deployable over Slack, Teams, intranet portals, or custom frontends, and includes logging, role-based access control, and compliance support.
Autonomous Tier-1 Support with Contextual Awareness
The Customer Support Fleet is a production-ready conversational Agentic AI layer over your product and support knowledge base. Designed for high-volume environments, it offers:
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Multi-turn dialogue management with contextual memory and intent handling
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Real-time integration with CRMs, ticketing systems, and product APIs
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Support for multilingual NLP and tone modulation
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Escalation protocols with full handoff context for human agents
With built-in analytics, fallback strategies, and adaptive learning, the agent enhances CSAT scores while reducing ticket resolution time and operational cost.