Conversation
Outbound and inbound voice agents, WhatsApp and web chat. Qualification, booking, follow-up and escalation, with the transcript in your CRM.
AI agents & automation
AI agents and automation that do real work.
Voice agents that make and take calls, assistants that answer from your own documents, and pipelines that read the paperwork nobody wants to retype. Connected to your CRM, inbox and phone system — not running in a sandbox.
What we build
The demo is easy. Production is the job.
Almost anyone can wire a language model to a chat box in an afternoon. The distance between that and something a business can rely on is where the actual engineering lives: what happens when the model is unsure, when the API is down, when the caller says something nobody scripted, and who gets the transcript afterwards.
Voice agents
We built an autonomous outbound caller for a US call centre that could only dial as fast as it could hire. It pitches naturally, qualifies the lead live, handles interruptions, and logs every warm lead where the sales team already works. Voice is the hardest surface to get right — latency, barge-in and turn-taking all have to feel human before the content matters at all.
Assistants grounded in your own content
A general model is confidently wrong about your business. Retrieval-augmented generation fixes that: your documents go into a vector store and the assistant answers only from them, with a citation back to the source. We have shipped this over stacks of PDFs nobody had time to read, and as a multimodal agent that examines an image, hears the question and speaks the answer.
Automation that is not a toy workflow
The highest-return automations are usually unglamorous. An invoice pipeline that watches a Drive folder, OCRs each document, extracts the fields and writes the books took most of a week back for a team of accountants. A property-intelligence pipeline turned an hour of hopping between maps and listings into one link in, verified contacts out.
Where we draw the line
Every agent we ship has a human handoff, a full transcript, and a defined behaviour when it does not know. Anything touching money, health or a legal obligation gets a person in the loop by design. An agent that cannot say "let me pass you to someone" is a liability, not a feature.
What you get
- Voice and chat agents that handle intake, triage and follow-up
- Wired into your CRM, inbox, calendar and phone system
- Human handoff and a full transcript on every conversation
- Grounded answers with citations, not confident invention
- Cost per conversation measured and capped, not discovered on the invoice
- A defined fallback for every failure mode, including the model being down
Stack we use
- OpenAI
- Anthropic
- LangGraph
- Whisper
- Twilio
- n8n
- FastAPI
- Vector DBs
How it runs
Three things we automate most often.
Different surfaces, same test: does it survive contact with a real user?
Documents
Invoices, forms, contracts and reports read by OCR and a model, fields extracted, and written into the system that needed them.
Back-office workflow
The chains of copy-paste between tools. Triggered, retried, logged, and monitored so a silent failure is not discovered a month later.
Selected work
AI agents we have shipped.
Every one of these started as somebody’s bottleneck. See all eleven projects.
Questions
AI agents & automation, answered.
What is the difference between an AI agent and a chatbot?
A chatbot replies. An agent acts — it can call your systems, look something up, book a slot, write a record, and decide it needs a human. The engineering that matters is not the conversation, it is the tools the agent is allowed to use and what happens when one of them fails.
Will an AI voice agent sound like a robot to my customers?
Not if latency and turn-taking are engineered properly, which is most of the work. The give-away is almost never the voice itself; it is the pause before the reply and the inability to be interrupted. Ask us for the demo and judge it yourself before you commit to anything.
Is my data used to train models?
No. We use providers on terms that exclude your data from training, and for sensitive workloads we can keep retrieval and storage entirely inside your own infrastructure. Which parts of a workflow touch a third-party API is documented before we build, not after.
What does it cost to run once it is live?
There are two costs: our build, and your per-use model and telephony spend. We measure cost per conversation during the build and put a hard cap in the configuration, so the running cost is a number you approve rather than a surprise at the end of the month.
Can it work with the tools we already use?
That is the point of it. HubSpot, Salesforce, Google Workspace, WhatsApp Business, your own database — if it has an API or a webhook, the agent can read and write to it. Integration work is the majority of every agent project we have shipped.
What happens when the agent does not know the answer?
It says so and hands over to a person, with the transcript attached so nobody has to start the conversation again. That behaviour is configured per workflow, and we test the handoff as carefully as the happy path.
More of what we do
The other five disciplines.
Most projects need more than one. They are in the same team, so nothing waits on a handover. See all services.
Web & software development
Custom web applications, platforms and internal tools, from first wireframe to production.
ExploreData engineering & ML
Pipelines, warehouses, dashboards and models built on the data you already have.
ExploreCloud & DevOps
Infrastructure as code, CI/CD and monitoring, so deploys stop being an event.
ExploreAPIs & integrations
Documented, versioned APIs and connections to the systems your business already runs on.
ExploreMVP development
From idea to a product your users can try, in four to eight weeks, built to grow.
Explore