AI products · agents & automation
AI that works on a Tuesday, not just in the demo
Production agents, RAG, and automations with the unglamorous parts that keep them honest: eval suites, cost dashboards, and a fallback for when the model has a bad day.
What this engagement actually looks like, start to ship.
Every AI build starts with a short paid discovery: we pin the use case, audit the data, and agree the eval bar before anyone quotes a line of code. Then we build in fixed-scope phases, each ending in a working demo you can actually try.
You get a production codebase with structured outputs, an eval suite of golden and adversarial cases, cost and latency dashboards, and human-in-the-loop fallback paths. Instrumented from day one, so you can always tell what changed and why.
Scoped, priced, and shipped before.
- AI voice agents · real estateAn AI voice agent for real estate that actually closes the loopBuyers and renters call at 9pm. An AI voice agent answers every one, qualifies the lead, books the viewing, and hands your agents a warm calendar instead of a missed-call list. Built by a team that ships production voice, not demos.See the build
- AI voice agents · restaurantsAn AI voice agent for restaurants that never lets the phone ring outEvery missed call is a missed booking. An AI voice agent answers every ring, takes the reservation, handles the “are you open on Sunday?” questions, and lets your floor staff run the room instead of the phone.See the build
- Automation · n8nAn n8n automation agency that builds workflows you can actually trust in productionWe design, build, and host n8n automations that move real work between your tools: self-hosted for data control, instrumented so you can see what ran, and built to survive the day an API changes. We run n8n ourselves.See the build
- AI voice agents · pricingWhat an AI voice agent actually costs to build and runEvery “AI voice agent pricing” page dodges the question. Here’s the honest structure of the cost, the one-time build versus the per-minute running cost, from a team that ships production voice agents, so you can budget before you talk to anyone.See the build
- Agentic AI · agentsAn AI agent development company that ships agents you can put in front of customersMost agent demos fall apart the first time a real user is vague. We build agentic AI with the unglamorous parts included: evals, tool-call guardrails, cost caps, fallbacks, and traces you can read when something goes wrong.See the build
- Generative AI · LLMA generative AI development company that builds features, not demosWe take a generative AI idea from "wouldn’t it be good if" to a feature inside your product, with the retrieval, the evals, and the cost controls that make it survive contact with real users.See the build
- Automation · AI opsAn AI automation agency that measures the hours it gives backWe find the process your team repeats by hand, automate it on infrastructure you own, and instrument it so you can see what ran, what failed, and what it saved. Starting at a price that does not need board approval.See the build
- AI chatbotsAn AI chatbot development company that builds bots your customers do not try to escapeGrounded in your actual content, honest when it does not know, and wired to hand off to a human before anyone gets annoyed. Deployed on your site, WhatsApp, or wherever your customers already are.See the build
- WhatsApp AI agentsA WhatsApp AI agent, because that is where your customers already areAnswers questions, qualifies, books, and hands off to a person, inside the app your customers open forty times a day. Live on the official WhatsApp Business API, roughly half the cost of the same thing on the phone.See the build
- WhatsApp automation · chatbotsWhatsApp automation that does the work, not just the replyingAnswer, qualify, book, update, and follow up inside the app your customers already have open, wired into the systems you already run. Official Business Cloud API, fixed price, live in weeks.See the build
- AI receptionistAn AI receptionist that costs less than the calls you are missingAnswers every call, books the appointment, takes the message, and passes a real person through when it matters. Published build prices, and an honest comparison against what a human receptionist actually costs.See the build
- Process automationA business process automation consultant who starts with the process, not the toolThe work your team does by hand every week because the systems do not talk to each other. We map it, cost it, automate the parts worth automating, and leave the rest alone. The platform gets chosen last, on purpose.See the build
Every potion, fully labeled.
- 01Agent or pipeline architecture doc
- 02Production codebase with structured outputs
- 03Eval suite (golden + adversarial cases)
- 04Cost & latency dashboards
- 05Prompt versioning and rollback flow
- 06Human-in-the-loop fallback paths
Boring tools, on purpose.
We pick tools for how they behave in year three, not for the launch-week demo. Here is what we reach for in this work, and the one-line reason each earns its place.
- Anthropic ClaudeOur default for reasoning-heavy work, called with structured outputs.
- OpenAIFor the fast-and-cheap paths where the reasoning bar is lower.
- LangChainOrchestration when a flow has real branching; plain code when it does not.
- pgvectorRetrieval that lives next to your relational data, not in a second bill.
- ModalOpen-weight models and heavy jobs, run where the data can stay put.
- LiveKitReal-time voice: barge-in, sub-second latency, the parts a demo skips.
- n8nAutomation plumbing between your tools when a full agent is overkill.
- SentryErrors and cost anomalies surface before your users find them.
Most AI software is a demo
Most “AI software” is a demo held together with duct tape: impressive in a screen recording, fragile the first time a real user does something unexpected. We build production systems instead: agents that handle real workflows, retrieval that actually retrieves, and the boring infra that tells you what changed and why.
The unglamorous parts, eval suites, prompt versioning, cost caps, human-in-the-loop fallbacks, are exactly what separate a shipped agent from a demo. They are in every build, not sold back to you as an upsell.
The right model, not the loudest
We work with the major providers, Anthropic, OpenAI, Google, and open-weight models via Modal or Together, and pick the one that fits your job, not the one with the biggest launch. Sensitive data can stay on open weights; reasoning-heavy work goes to Claude; fast-and-cheap paths go elsewhere.
Where the work is well understood enough to productize, we publish the price instead of quoting it. The AI voice and automation solutions are the same engineering, packaged.
Not claims. Shipped work.
- 12,000+
- students onboarded in season one
- 87%
- guided-flow completion
- 4.8★
- avg user rating
- < €4
- avg AI cost per student
Chatberry — AI WhatsApp marketing platform
An Arabic-first WhatsApp marketing platform: AI-powered chatbot, bulk official-WhatsApp messaging, multi-agent shared inbox, interactive buttons and rule-based reply automation — a complete WhatsApp marketing toolkit.
Ashpulp Technologies — AI / data / dev studio
A studio marketing site for Ashpulp Technologies — a digital partner combining data analytics, AI, marketing and web/software development. The site reports 40+ delivered projects, 5+ AI-powered builds and three years of practice.
AI Calling Agent — outbound AI voice ops
An outbound AI voice product with a back-office dashboard for ops: Dashboard, Calls, Transcriptions, AI Agents, CRM, Users and Settings — the full operational surface for running and analysing voice campaigns.
Parcoursup Zen — AI orientation for French post-bac
A French-language guidance platform that helps post-bac students navigate Parcoursup. AI matches student profiles against 23,000+ formations, tracks application deadlines, drafts motivation letters, and offers a chatbot for orientation questions.
ReadyShortlist — vetted tech talent in 72 hours
An end-to-end product for Pakistan’s vetted tech-talent network — marketing site plus admin portal for managing candidates, employers, briefs, the candidate funnel and a 5-point vetting workflow that ships interview-ready shortlists in 72 hours.
Read first, then talk to us.
- Vapi vs RetellTwo hosted voice platforms compared, and when to outgrow both.
- n8n vs ZapierWhere no-code automation ends and a real agent begins.
- AI voice agent pricingWhat a production phone agent actually costs to build and run.
- Free Claude Code packsThe MIT-licensed tools we ship, if you’d rather build it yourself.
How we scope and price
Bespoke AI builds are priced to their real risk, not a fixed menu. We pin the use case, the data, and the eval bar first, then quote a fixed-scope build you can plan around. Where the work is well understood enough to productize, we publish the price instead: see the solutions pages.
- A short paid discovery: use case, data audit, eval targets
- Fixed-scope build phases, each ending in a working demo
- Instrumented from day one: cost and latency dashboards
- Ongoing support or a clean handover; your call
Tell us the use case and we’ll scope shape, timeline, and cost together on a quick call.
Common questions.
01What does an AI agent development company actually do?
We take an agent from use case to production: a short paid discovery to pin the workflow and data, an architecture with structured outputs, an eval suite (golden + adversarial cases), cost and latency dashboards, and human-in-the-loop fallbacks: then a clean handover or ongoing support. The unglamorous parts (evals, cost caps, fallbacks) are what separate a shipped agent from a demo.
02Do you build custom AI agents, or wire up no-code tools?
Both, honestly scoped. For a well-defined workflow, a no-code automation (n8n or Make) can be the right and cheapest answer, and we will tell you so. When the agent is core to your product (bespoke logic, real reliability targets, or data you cannot hand to a third party), we build a custom, instrumented agent you own outright.
03Which model providers do you use?
Anthropic Claude is our default for reasoning-heavy work. OpenAI for fast-and-cheap. Open-weight models on Together or Modal for sensitive data or cost-sensitive workloads. We mix where it makes sense.
04How do you handle cost overruns?
We instrument every call from day one. Per-customer cost dashboards, hard daily caps, automatic graceful-degradation when budgets are approached.
05How much does it cost to build an AI product?
It depends on the surface area: a single well-scoped agent or RAG feature is a few weeks; a full product with evals, dashboards, and fallbacks is more. We start with a short paid discovery to pin the use case and data, then quote a fixed-scope build so there are no surprises.
06How long does an AI build take?
Most first versions ship in 4–8 weeks: discovery, a working demo, then hardening (evals, cost/latency dashboards, human-in-the-loop fallbacks). We ship a usable demo early rather than disappearing for a quarter.
07Are you an AI automation agency or an AI agent development company?
Both: the two overlap more than the labels suggest. As an AI automation agency we wire up workflows (n8n, Make, custom code) that move work between your tools; as an AI agent development company we build agents that reason and act inside those workflows. Most engagements are a mix: an agent doing the thinking, automation doing the plumbing.
08What are agentic AI development services?
Agentic AI development means building systems where an LLM decides what to do next (calling tools, retrieving context, and looping until a task is done) rather than following a fixed script. Our agentic AI development services cover the architecture, the tool-calling and memory layer, the eval suite that keeps it honest, and the cost caps that keep it affordable in production.