AHK.AI operates intelligent customer support systems. We deploy managed AI agents that resolve tickets, route complex cases, and integrate with your CRM—governed by strict SLAs and human-in-the-loop oversight. We don't just build chatbots; we architect the workforce that runs your front line.
Full conversation analytics & quality assurance dashboard
Operator Training for Human-in-the-Loop handoffs
How We Deliver This Service
Our consultant manages every step to ensure success:
1
Interaction Mapping: analyzing your top 100 call/ticket drivers.
2
Dialog Architecture: Designing the state machine for complex resolution flows.
3
Integration & Knowledge Engineering: Connecting APIs and ingesting SOPs.
4
Voice & Tone Tuning: Ensuring the AI speaks your brand language.
5
Shadow Mode: Running safely alongside humans to validate accuracy.
6
Live Orchestration: Phased rollout with active monitoring.
Technologies & Tools
OpenAI GPT-5.2 Anthropic Claude 3.5 Vapi / Retell AI (Voice) Amazon Connect LangGraph (Orchestration) Pinecone (Memory) Segment (CDP)
Frequently Asked Questions
What happens if the AI doesn't know the answer?
We prioritize 'Zero False Positives'. If confidence is low, the AI seamlessly transfers the chat (with full context summary) to a human agent, or opens a ticket. It never guesses.
Can it take actions, or just talk?
It takes action. We integrate with your APIs to process refunds, update addresses, cancel subscriptions, or reset passwords directly. Every action is logged and governed by business rules.
Is Voice/Phone support included?
Yes, in Standard and Premium tiers. We use ultra-low latency models (like Vapi) to enable natural, interruptible voice conversations that feel human, completely replacing legacy IVR trees.
How do you handle 'angry' customers?
Our sentiment analysis runs in real-time. If it detects frustration or escalation keywords, the AI can apologize and immediately route the user to a priority human queue, bypassing standard triage.
Does it improve over time?
Yes. We implement a 'Feedback Loop' where human agents rate AI drafts or interventions. This data is used to fine-tune the prompts and knowledge base weekly, increasing the containment rate continuously.
Client Reviews
★★★★★ 5
based on 145 reviews
★★★★★ 5
Deflected tickets fast
We launched an order-status and returns assistant on our Shopify storefront and in Slack for the CX team. AHK.AI trained the NLU on our product taxonomy and shipping policies, then set up RAG over our help docs plus carrier tracking pages. Within two weeks, it was resolving “where’s my order” and “exchange vs refund” questions with surprisingly accurate answers. The handoff to Zendesk is clean, with context and customer email prefilled. Ticket volume dropped noticeably without hiring.
Project: Shopify + Zendesk customer support virtual assistant with RAG over shipping/returns documentation
★★★★★ 5
Better triage, fewer pings
Our support queue was getting crushed by “how do I…” questions and noisy bug reports. AHK.AI implemented dialog flows for troubleshooting, plus RAG over our Confluence KB and release notes. The assistant lives in Intercom and Teams, and it tags issues by module and severity before creating Jira tickets. The NLU handles our feature names and acronyms without constant retraining. We saw faster first response times and cleaner tickets, which made engineering a lot happier.
Project: Intercom + Jira + Confluence conversational assistant for support triage and self-serve troubleshooting
★★★★ 4.5
Strong internal helpdesk
We used AHK.AI for an internal HR/IT assistant for a multi-clinic organization. It answers policy questions (PTO, credentialing, benefits) via Teams, using RAG over our HR handbook and SOPs. Security and access controls were handled carefully, which mattered for our compliance posture. The only reason it’s not a perfect score is we needed extra iteration on medical role terminology and scheduling edge cases. Once tuned, it reduced repetitive calls to HR significantly.
Project: Microsoft Teams virtual assistant for HR policies and internal support with role-based access
★★★★★ 5
Leads handled 24/7
We wanted a conversational assistant that could qualify inbound leads on our website and route them to the right agent based on zip code and price range. AHK.AI built the dialog management, connected it to our CRM, and pulled property details from our listings feed using RAG for neighborhood FAQs. It schedules showings and captures buyer vs. seller intent without sounding robotic. Agents now start calls with context instead of chasing basic info.
Project: Website chatbot integrated with CRM for lead qualification, listing Q&A, and showing scheduling
★★★★ 4
Secure, needs fine-tuning
We deployed a client-facing assistant for common banking questions and internal procedures. AHK.AI did a solid job with enterprise security requirements and building RAG over our policy library and product sheets. It integrates with our ticketing system for escalations and keeps an audit trail, which our risk team appreciated. The gap was around nuanced regulatory phrasing—some answers needed stricter guardrails and more explicit citations. After adjustments, it’s reliable for tier-1 queries.
Project: Secure conversational assistant for retail banking FAQs and internal policy lookup with ticket escalation
★★★★★ 5
Stops the Slack chaos
Our team was drowning in “where’s the latest deck / brief / KPI report” messages. AHK.AI built a Slack assistant that uses RAG across Google Drive folders, Notion pages, and SOP docs, with permissions respected. The NLU understands client codenames and campaign jargon (UTMs, ROAS, creative variants). It can also open a task in our PM tool when someone asks for a new landing page or ad refresh. It’s like having an ops coordinator on-call.
Project: Slack-based knowledge assistant for agency deliverables, SOP retrieval, and task creation in PM tooling
★★★★ 4.5
Great for shop-floor
We needed quick answers to work instructions and maintenance procedures without digging through PDFs. AHK.AI set up a kiosk-friendly web assistant and a Teams bot for supervisors. The RAG pipeline indexes our SOPs, BOM notes, and safety documentation, and the dialog flows guide operators through lockout/tagout steps and troubleshooting. It also logs incidents into our ticketing system. Occasionally, older scanned documents required cleanup for better retrieval, but overall it’s been a big efficiency win.
Project: Web + Teams assistant for SOP retrieval, safety guidance, and maintenance ticket logging
★★★★★ 5
Proposal engine booster
We engaged AHK.AI to build an internal assistant for consultants to draft SOW sections and answer methodology questions. It uses RAG over past proposals, case studies, and our delivery playbooks, and it’s accessible in Teams. The NLU picks up our service line terminology and can recommend relevant artifacts based on industry and scope. It doesn’t replace judgment, but it saves serious time on first drafts and reduces “who has the latest template” hunting.
Project: Internal Teams assistant for proposal/SOW drafting support using RAG over templates and prior engagements
★★★★ 4.5
Helps students self-serve
We rolled out a virtual assistant for a university department to handle advising FAQs and administrative questions. AHK.AI trained the NLU on course codes, prerequisites, and policy language, and built RAG over our catalog, advising guides, and scholarship pages. It runs on the website and in Teams for staff. Students get accurate answers on deadlines and forms, and complex cases are routed to our ticketing queue with context. Minor tuning was needed around exceptions in degree audits.
Project: Multi-channel assistant for advising and admin Q&A with escalation to department ticketing
★★★★★ 5
Cuts WISMO calls
We operate regional freight and last-mile delivery, and customers kept calling for shipment updates. AHK.AI built a web and voice-friendly assistant that pulls tracking events from our TMS and answers lane-specific questions (POD, appointment windows, accessorials). The RAG layer covers our service terms and claims process, so responses stay consistent. It also opens a ticket when there’s an exception scan or missed ETA. Dispatch now focuses on real issues instead of constant status checks.
Project: Customer-facing assistant integrated with TMS for tracking, exception handling, and claims/ticket creation
