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Trident Square

AI Agent Development

Prong
02 — Thinks
Timeline
First working agent in 3–5 weeks
Engagement
Fixed scope or team

AI agents that do the work, not just the talking

We design and ship AI agents that plug into the systems you already run — your CRM, inbox, WhatsApp, sheets and internal APIs — and take real actions with guardrails, logs and a human in the loop where it matters.

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Gigtap — built with AI Agent Development
Built with ai agents & automation — Gigtap →

01 / Why it matters

Most “AI projects” stall at the demo. The hard part is everything after: connecting the agent to live data, making it reliable on messy inputs, deciding when it should hand off to a person, and proving it saves time. That is the part we specialise in.

We start with one workflow that costs you hours every week — lead qualification, support triage, document processing, scheduling — map it step by step, then build an agent that handles it end to end. You get evaluation sets, cost tracking per run and an admin view, so you can see exactly what the agent did and why.

02 / What you get

  1. 01Workflow audit and an agent design you can read in one page
  2. 02Tool-calling agent connected to your APIs, CRM and messaging channels
  3. 03Retrieval (RAG) over your documents with source citations
  4. 04Evaluation suite, guardrails and human-handoff rules
  5. 05Admin dashboard: conversations, actions, cost per run
  6. 06Deployment on your cloud or ours, with monitoring

03 / Where it pays off

Common use cases

01

Lead qualification

Agent replies to inbound leads in seconds, asks the right questions and books qualified calls into your calendar.

02

Support triage

Reads tickets and chats, answers from your knowledge base, escalates edge cases with full context.

03

Back-office automation

Extracts data from invoices, forms and PDFs, validates it and pushes it into your ERP or sheets.

04

Internal copilots

Lets your team query company data in plain language — orders, inventory, policies — with permissions.

Tools we use — OpenAI / Anthropic Claude / Gemini / LangGraph / Python / Node.js / PostgreSQL + pgvector / n8n / AWS

04 / Proof

Related work

AI Agent Development — FAQ

Questions, answered.

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  1. A focused agent for one workflow typically starts around ₹3–6 lakh (US$4k–8k) for the first production version. Multi-agent systems with several integrations cost more. Running costs (model usage and hosting) are estimated up front and shown per run in the dashboard.

  2. Whichever fits the job. We benchmark OpenAI, Claude and Gemini on your real data and pick on accuracy, latency and cost. The agent is built so the model can be swapped later without a rewrite.

  3. Your data stays in your accounts where possible. We use providers that do not train on API data, restrict the agent to the permissions it needs and log every action for audit.

  4. It hands off. Every agent we ship has explicit confidence thresholds and escalation rules — to a person on WhatsApp, email or your helpdesk — with the full conversation attached.

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