Dedicated full-time
Owns the agent, its tools, evaluations and monitoring. Best when automation is a core part of your roadmap.
Taking on new projects · We reply within 24 hours on business days
Dedicated AI agent engineers
Want an agent that reads a ticket, looks up the order, drafts the refund and waits for approval? DayDecoder hires AI agent developers from Ahmedabad, India who connect models to your real systems through narrow tools, log every step, and keep a person in the loop wherever money or customers are involved. Overlap hours for the US, UK, Europe and Australia.
An agent is a model that can take actions through tools. The hard part is not the prompt; it is deciding which actions are safe, logging them, and stopping when something looks wrong.
Our public work is the foundation for this. The WhatsApp marketing SaaS runs chatbot flows and OpenAI-assisted replies inside a shared team inbox. The AI customer support assistant produces ticket summaries, suggested replies, knowledge search and escalation recommendations. The document intelligence platform extracts and classifies data with review queues. The CRM workflow automation engine and data sync dashboard move records between systems on queues. An agent hire combines these pieces: the model decides the next step, and code we write decides whether that step is allowed.
We are careful with the word autonomous. None of the projects on this site let a model move money or message customers without a rule or a person approving it, and we would design yours the same way. Many briefs that start as an agent end up as a well-defined workflow with one or two model calls, which is cheaper and easier to trust. We will say so when that is the better answer.
Each tool does one thing, such as look up an order or create a draft, with validated inputs and permissions checked in your code, not in the prompt.
Refunds, outbound messages and record changes wait in a review queue until a person accepts, edits or rejects them.
Every model call, tool call, input and result stored, so you can see why the agent did what it did and replay a bad run.
Step limits, token budgets, timeouts and fallbacks to a human when the agent is unsure or a provider is down.
Skills and tool stack
Models from OpenAI or Claude, orchestration that stays readable, and the queue and database patterns we already use in production.
Agents usually run as queued jobs in Laravel, Node.js or Python, call the model through the provider’s function or tool-calling interface, and record each step in your database. LangChain or LlamaIndex are used when they reduce code; otherwise we use the provider SDK directly. Retrieval is added when the agent needs your documents, following the same rules as our RAG work.
Engagement models
Agents need tuning after launch, so most clients keep the same engineer for a while.
Owns the agent, its tools, evaluations and monitoring. Best when automation is a core part of your roadmap.
Reserved days each week to extend one agent at a time, review its logs and adjust its limits.
A review of an agent that misbehaves, a cost spike, or a second opinion on whether you need an agent at all.
Hiring process
We begin with the action the agent must never take, then work backwards.
Thirty minutes with the founder about the task, the systems involved and the mistakes that would be expensive.
Dedicated, part-time or hourly, and whether an agent, a fixed workflow or no AI at all is the right first step.
API keys and data stay in your accounts. The agent gets its own scoped credentials, never a person’s login.
One task end to end, with every action going to a review queue and a small evaluation set to measure it.
Logs, approval rates, cost for the week and what we will let the agent do next, in your overlap hours.
We work from Ahmedabad, India. Agents can process queues overnight in your time zone, while approvals and reviews happen in your working day. Afternoons overlap with the UK and Europe, early mornings or late evenings with the US, and mornings with Australia.
If a model provider has an outage, the agent hands work to a person rather than guessing. That fallback is part of the design, not an afterthought.
Morning updates waiting in your inbox when the US workday starts.
Same-day overlap for calls, reviews, and decisions.
Afternoon overlap with Central and Eastern European teams.
Early-morning calls that fit the Australian workday.
Product engineers who already build automation, AI assistants and review queues, and who would rather limit an agent than apologise for it.
Workflow engines, data sync and chatbot flows are in our public work, so agents start from proven patterns.
Permissions, limits and approvals are enforced by the application, where they cannot be talked around.
If a simple workflow beats an agent, we build the workflow and tell you why.
Prompts, tools, logs and evaluation sets are yours after payment. Your data is never used for other clients.
Relevant work
Projects with chatbot flows, AI-assisted replies, review queues and workflow automation. Client names stay confidential.
A multi-tenant SaaS that lets businesses run WhatsApp marketing and support from one console: template campaigns, a shared team inbox, contact management, chatbot flows and AI-assisted replies, sold on subscription plans.
A technical guide on how to integrate AI features (OpenAI, Anthropic) into existing Laravel and Node.js SaaS products using vector databases and background queues.
When to choose custom AI software development versus buying SaaS AI tools: data advantage, process rules, review needs, and cost tradeoffs.
Architecture, RAG, cost control and security for adding OpenAI or Claude to a production Laravel or Node.js app, written for overseas founders and CTOs.
FAQ
Straight answers on the stack, ownership and time zones. Email us if yours is missing.
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