Response intelligence API
One call takes the context of a live conversation, predicts what the person is actually trying to do, and returns a response tuned for style, accuracy and resolution. Point it at the sales, service or support system you already run and it works there.
Works on the channels you already have
Access
Tell us where Humoniq would sit in your stack and we will send the technical detail, the access terms and a sandbox key. Four fields, and we will take it from there.
We read every request ourselves. No autoresponder, no drip sequence, no sales cadence.
Endpoint reference, rate limits, data handling terms and pricing for the volume you described.
If it looks like a fit, a key and a worked example running against interactions of your own.
Prefer email? Write to access@humoniq.com and tell us the same four things.
Pipeline
Three stages, one request. You send the interaction with whatever context you hold on it, and Humoniq works through intent, options and wording before anything comes back.
01
Humoniq reads the interaction in context: the thread so far, the account behind it, the channel it arrived on and how long it has been waiting. It works out what the person is actually trying to do, which is rarely the same as what they typed.
02
That intent gets mapped onto what can realistically happen next. The answer to give, the record to update, the offer that actually fits this account, the escalation that saves someone an hour on Monday.
03
The draft is scored and rewritten until it holds up on style, accuracy and solution, then returned in the shape your system already expects. Nothing leaves the API until it beats the version before it.
You ask for what you want in the request and the same endpoint returns it. Most teams end up using all three, on different queues.
Send the agent draft and Humoniq returns it sharpened, with the gaps filled and the tone held steady.
No draft needed. The response comes back complete and ready to send, or to hold for review.
Structured next actions with confidence attached, for the agent to approve or your system to run.
Scoring
Every draft is scored on three factors before it is allowed out. A reply that is warm but wrong fails. So does one that is correct, complete and takes four days to arrive.
The response that ships is the one holding all three at once. Drop any single factor and the reply stops being worth sending.
Does it help, does it sound like a person worth talking to, and does it get there in as few words as the point actually needs?
Are the technical details right, is every question in the message accounted for, and is it written in the language the customer wrote in?
Does the reply move the thing forward? A clear next step, an action genuinely taken, and an answer that arrives while it still matters.
Surface area
Humoniq is a plain HTTPS endpoint with no opinion about what sits in front of it. If your system can send the text of an interaction and receive JSON back, it works. There is no plugin to wait for and no platform to migrate to.
Follow-ups, qualification replies and renewal conversations in whatever pipeline you already run, B2C or B2B.
Ticket replies drafted against the full thread, with the suggested action attached to the ticket rather than lost in a note.
Short-turn conversations where latency is the product. Same call, tighter output budget.
Long threads with quoted history, multiple participants and three questions buried in the fourth paragraph.
Send a transcript, get back the wrap-up summary, the follow-up message and the actions the call implied.
The custom admin panel nobody outside your company has heard of works exactly as well as the ones that do.
Sales, service and support all run through the same call. The difference is the context you send with it. B2C or B2B, ten agents or a thousand, the request body does not change shape.
See what to sendDifference
There is no shortage of ways to send a customer a message faster. Almost all of them get faster at sending the same message.
Macros and templates freeze one good answer in place. The tenth customer gets a reply written for the first, the phrasing that stopped working six months ago keeps going out, and nobody notices until the complaints do. Humoniq writes against the interaction in front of it, every single time, and a near-identical question from a different account can correctly get a different answer.
What got a reply, what closed, what came back a second time, what got escalated anyway despite a confident answer. Those signals feed the scoring rather than sitting in a report nobody opens. The responses your team sends in six months will not be the ones it sends today, and you will not have rewritten a single template to get there.
Same five customers, same five questions. On the left, five copies of one answer. On the right, five responses shaped by who asked, what they already know, and what happened last time someone asked it.
Our purpose
Humoniq started with a bad support thread. One of us spent three weeks trying to sort out a billing error, and every message back was a slightly reworded version of the last, technically responsive and completely useless, clearly assembled from a template by someone who had no room to think. The frustrating part was knowing the fix was small, and suspecting the person on the other end knew it too. That is the gap we build for. Not replacing the people who answer, but handing them a system that understands what was actually asked and returns something worth sending, so the customer gets an answer instead of an acknowledgement. Delight is not a feature bolted on at the end. It is what is left over when nobody has to repeat themselves.
The Humoniq team
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