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Your Support Queue is Drowning Your Team. We Build the AI That Takes Over.

If you're a VP of Ops watching ticket volume spike faster than hiring approvals, you need conversational AI that closes tickets and converts leads without a single new FTE.

We build conversational AI systems that handle customer service at scale and turn visitors into qualified leads -- 24/7, no extra headcount required.

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AI Chatbot Development

AI chatbot development is the process of building, training, and deploying conversational agents that can handle real support and sales workflows on their own -- no hand-holding required. Here's the thing most people miss: there's a massive difference between dropping a generic bot on your site and actually building one that knows your business. A custom-built system gets trained on your specific knowledge base, your brand voice, the way your team actually talks to customers, and your escalation logic -- who gets the handoff, when, and why. We've built these for SaaS companies in Austin, e-commerce brands running out of London, and professional services firms that thought automation would never work for them. It does, when it's built right. The result isn't a bot that makes customers want to throw their laptop across the room. It's one that closes tickets, qualifies leads, and only escalates when it genuinely should. That's what separates a well-engineered chatbot from the ones that make people click "speak to a human" in the first 30 seconds.

What is holding your current website back?

Common gaps we find in nearly every audit.

Tier-one tickets -- password resets, order status checks, basic troubleshooting -- are eating up senior support staff who should be handling the cases that actually need human judgment
Risk: And the downstream effects compound fast. Agent burnout climbs, resolution times stretch out, CSAT scores start sliding, and by the time headcount approvals clear HR, you've already lost three good people.
Someone lands on your pricing page at 2am, has a specific question, and leaves
Risk: That's a high-intent lead -- gone. They're talking to a competitor by morning, and your CRM doesn't even have a record that they showed up. It happens every night, and it's entirely preventable.
Off-the-shelf chatbot platforms are fine until someone asks anything slightly outside the FAQ script
Risk: Then you've got a bot spinning in dead-end loops, customers getting frustrated, and escalation rates climbing -- which ironically means more work for the team you were trying to give breathing room. Worse, it poisons the well. Once users decide your bot is useless, they'll never trust it again.

How We Build This Right

Every safeguard, built in from Day 1.

Data Residency Controls

Conversation data gets processed and stored according to your specific regional requirements -- GDPR, HIPAA, whatever your legal team has flagged. We support on-premise deployment or private cloud setups for organizations where data sovereignty isn't optional. It's not an afterthought; it gets scoped in week one.

Role-Based Access Management

Admin, editor, and analyst roles are enforced at the platform level. So the person pulling conversation reports can't accidentally -- or intentionally -- modify intent logic or overwrite training data. Only the right people can touch the right things, and that's baked into the architecture, not bolted on after the fact.

Audit Logging and Reporting

Every config change, every model update, every escalation event gets logged with a timestamp and a name attached to it. Compliance teams get a full audit trail without anyone manually tracking anything. When an auditor asks what changed and who changed it, the answer is already there.

What We Build

Purpose-built features for your industry.

Domain-Specific Model Training

We fine-tune or prompt-engineer GPT-based models directly against your support documentation, product catalog, and historical ticket data. The real kicker here is context -- a generic LLM will hallucinate plausible-sounding nonsense because it's guessing. Your bot answers accurately because it's working from your actual source material, not vibes.

CRM and Help Desk Integration

Native connectors for HubSpot, Salesforce, Zendesk, and Intercom mean the bot isn't just chatting -- it's doing work. Creating tickets, updating contact records, triggering follow-up workflows, all mid-conversation, without anyone on your team touching it. That's where the real time savings show up.

Escalation Routing with Context Handoff

When a conversation goes outside what the bot's built to handle, it doesn't just drop the customer into a queue with nothing. It transfers the full chat history, the detected intent, and the relevant customer record to the right human team. So the agent picks up exactly where the bot left off. Nobody asks the customer to repeat themselves. Honestly, that handoff experience alone is worth the build cost.

Conversation Analytics Dashboard

The reporting layer surfaces the numbers that actually matter -- containment rate, where conversations drop off, clusters of unresolved intents, lead qualification volume. It's not vanity metrics. It's the data that tells you what to retrain next and lets you draw a straight line between bot performance and what it's costing you in baseline ticket volume.

Built on a Modern, Secure Stack

Next.jsOpenAI APILangChainVercel AI SDKSupabasePineconeVercel

Our Development Process

From discovery to launch. Quality at every step.

01

Discovery and Scope Definition

1 week

Before we write a single line of code, we audit your existing ticket categories, escalation paths, CRM configuration, and knowledge base. We're figuring out which workflows the bot should fully own, which ones need a human in the loop, and -- critically -- what "resolved" actually means for your team. That definition varies more than you'd think.

02

Data Preparation and Model Configuration

1-2 weeks

We take your support docs, FAQs, and product data and structure them into a proper training corpus. Then we configure intent classification and build the prompt architecture that governs how the model responds -- keeping it accurate, on-brand, and inside your policy guardrails. This is where most DIY chatbot projects fall apart, so we spend real time here.

03

Integration Build and Internal QA

1-2 weeks

We connect everything -- your CRM, your help desk, your deployment channel, whether that's a website widget, Slack, SMS, or a direct API integration. Then we run structured QA against actual historical ticket samples. Not synthetic test cases. Real conversations your team has already had, so we know exactly how the bot behaves before any user ever sees it.

04

Staged Launch and Handover

2 weeks

We go live to a controlled traffic segment first -- usually 10-20% -- and monitor containment rates and error patterns for two weeks. We retrain on whatever gaps show up in the wild. Then we hand over full documentation, admin access, and a retraining protocol your team can run themselves, no agency dependency required.

Social Animal

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Frequently Asked Questions

Single-channel deployments with RAG-powered knowledge retrieval and CRM integration start at $8,000. Multi-channel builds -- with advanced lead qualification flows and a custom analytics dashboard -- typically land between $14K and $25K. Where you fall in that range depends on how many integrations you need, how complex your conversation flows are, and the size of your knowledge base going in.
Most builds go live in five to six weeks. Discovery and conversation design in week one, development and integration through weeks two to four, then testing and prompt tuning in week five. If you've got a lot of integrations or you're deploying across multiple channels simultaneously, budget for eight weeks. We'd rather tell you that upfront than slip a deadline.
We use retrieval-augmented generation to anchor every response in your actual documentation rather than the model's general training. Stack that with prompt guardrails, output validation, and confidence scoring, and hallucination rates drop below 5% in practice. And when the bot isn't confident? It escalates. It doesn't guess.
Yes -- HubSpot, Salesforce, Pipedrive, and honestly most CRMs with a REST API are fair game. Lead data, conversation transcripts, and qualification scores sync automatically. On the helpdesk side, Zendesk, Intercom, and Freshdesk are all supported out of the box without custom middleware.
Absolutely. This isn't a SaaS platform where you're renting access to your own bot. You own the codebase, the trained knowledge base, and every conversation record. We deploy to your infrastructure or your Vercel account. No vendor lock-in, and no pricing that balloons the moment your conversation volume picks up.
We track ticket deflection rate, lead qualification conversion, average resolution time, drop-off points, and user satisfaction scores -- all in a custom analytics dashboard built for your setup. That data isn't just for reporting. It's what drives the prompt and flow tuning we do throughout the 30-day post-launch period. So the bot you have at day 30 is measurably better than the one that went live on day one.
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