I scope the system, choose the models, build it, and hand you something your team can actually run. Fixed-scope builds or ongoing retainers — remote, worldwide.
Customer-facing assistants that answer from your own content instead of hallucinating. Embeddable widgets, multi-turn tool use, and a clean handoff to a human when it matters.
shipped: Chatter AI · ChatterCraft AI · LawGPT · LawGuru
Your customers already live on WhatsApp. AI agents that answer there — domain-trained, always on, and cheap enough to run on a small VPS instead of a GPU cluster.
shipped: NBC 2016 WhatsApp assistant · FactoryBrainAI WhatsApp alerts · Chatter AI
Phone agents that hold a real conversation in Hindi and English — qualifying leads, booking appointments and handling inbound calls without a queue.
shipped: Mona @ RnDynamos Labs · bolna-ai/bolna · ArduPilot Assistant
The go-to-market machine, built like software: enriched lead lists, personalised cold outreach at volume, and instrumentation so you know what actually converts.
shipped: Lead Enrichment Tool · Automechnica outreach server · Daily cold email engine
The boring, expensive, manual work — gone. Internal tools, Slack bots, scheduled jobs and n8n pipelines that quietly run the business.
shipped: slack-claude · AI DevOps Agent · Cloudflare Tunnel + n8n @ Data Alt Dynamics
Making your tools actually talk to each other. Enterprise systems, SaaS APIs, CRMs, databases and AI — connected with auth, retries and error handling that hold up in production.
shipped: Enterprise integrations @ TAP Innovations · archestra-ai connectors · Google Calendar & Firebase integrations
Agents that plan, use tools, remember, and know when to stop and ask a human. Orchestrated with LangGraph so the control flow is explicit instead of vibes.
shipped: archestra-ai/archestra · AI DevOps Agent · slack-claude
Answers with receipts. Vector search over your documents, wikis and drives, wired into whichever model you want to use.
shipped: LawGPT · archestra-ai connectors · ChatterCraft AI
Custom Model Context Protocol servers that give agents real, safe access to your systems — plus the internal tooling that makes an AI-native team fast.
shipped: QuickDocs · AI DevOps Agent · archestra-ai/archestra
The difference between a demo and production. Tracing, eval suites, prompt versioning, and the cost and latency work that stops your AI feature bankrupting you.
shipped: Production RAG at Loadshare · archestra-ai · Chatter AI
Zero to shipped. Full-stack AI products built the way an AI-native team builds them — fast, with Claude Code and Cursor in the loop, and deployed for real users.
shipped: Chatter AI · QuickDocs · LawGPT
Generative Engine Optimisation — getting your brand cited by ChatGPT, Claude, Perplexity and AI Overviews, not just ranked on page one. Structured data, llms.txt, and content built to be quoted.
shipped: This site
AI that moves things. ROS2 control stacks, robot arms, IoT sensor networks and live factory dashboards — from firmware all the way up to the browser.
shipped: BCN3D Moveo · SCARA Robot · FactoryBrainAI · UK Design Patent 6450987
Book 30 minutes at cal.com/ayuugoyal. You tell me the problem; I tell you straight whether AI is the right answer, what it would take, and what it would not solve.
Fixed scope, working software early. You see progress continuously instead of waiting through a long silent build, and you can steer it.
Deployed, documented, and handed to your team — or kept on a retainer if you would rather I keep running it.
I take a business problem and design the whole system around it — which model, what retrieval, which tools the agent gets, how it fails safely, where it plugs into your existing stack — and then I build and ship it. Not a slide deck: working software you can put in front of customers.
Yes. I work with founders and teams on fixed-scope builds and ongoing retainers, fully remote, and I already work remote for a US-based team. Book a call at cal.com/ayuugoyal or email ayushgoyal8178@gmail.com with what you are trying to build.
Yes. I ship bilingual voice agents that handle inbound and outbound calls, qualify leads and book appointments, with telephony integration and transcripts synced back to your CRM.
A go-to-market engineer builds the revenue machine as software instead of manual work — enriched lead lists, personalised outbound at volume, and the instrumentation to see what converts. Same engineering rigour, pointed at pipeline instead of product.
Almost always. I build provider-agnostic, with Claude, OpenAI or Gemini selected by config, and I have shipped across Next.js, FastAPI, Flask, Express, Postgres, MongoDB, Docker, AWS and Azure. If you are already on something, I build into it rather than around it.
Yes, and it is the part I like most. ROS2 control stacks, robot arms, IoT sensor networks and live dashboards. I hold a UK design registration for a pneumatically actuated four-finger robotic gripper, and I run Physical AI projects through RnDynamos Labs.
Yes. I have shipped WhatsApp assistants built on FastAPI and Gemini that answer domain questions over a client's own documentation, run cheaply on a small VPS, and push live alerts and shift reports to a WhatsApp group. The same agent brain can also power a web chat widget.
That is most of the job. I connect Slack, WhatsApp, Gmail and Google Workspace, Notion, SharePoint, OneDrive and Drive, CRMs, calendars and internal databases — with OAuth, retries, rate limiting and error handling built in, so the integration does not quietly break at 3am.
Book a free 30-minute scope call at cal.com/ayuugoyal. We work out whether the problem is actually worth automating. If it is, I scope it into something shippable, and you get working software early rather than a long silent build.