AI Agent Agency That Works Around the Clock
An AI agent is not a chatbot that regurgitates your FAQ page. Tkist AI agent development services build production-grade agents that read context, make decisions within a defined boundary, take actions across multiple systems, and hand off to a human at exactly the right moment, our agency has built this in production, not in a demo environment.
0/7
Agent availability
0 min
Avg lead qualification time down from 4 hours
0%
Avg support tier-one deflection rate
The Problem
The gap between what chatbots promise and what AI agents actually deliver
Most businesses with chat widgets use static scripts built on yes/no decision trees. They annoy visitors, fail on any question outside the script, and convert almost nobody. A real AI agent understands your product, knows your pricing and objections, qualifies leads against your ICP, books discovery calls, and escalates to a human only at exactly the right moment. The conversion gap between a scripted chatbot and a trained AI agent is measured in multiples, not percentages.
We train agents on your actual product documentation, pricing, past sales conversations, and competitor positioning. The result is an agent that responds like your best salesperson at 3am on a Sunday, across every channel at once.
24/7
Agent availability
What's Included
Everything inside your ai agents & gpt builds package
See Full ScopeLead Qualification Agents
Agents that read, score, and route inbound leads via email or chat without human review.
Customer Support Agents
First-line support agents trained on your knowledge base, escalating to humans outside scope.
Internal Knowledge Agents
Ask questions against your documentation, SOPs, and data via a natural language interface.
Multi-Step Workflow Agents
Agents with tool use, CRM updates, calendar booking, email send, Slack notifications.
RAG Pipelines
Retrieval-Augmented Generation pipelines for grounded, document-cited responses.
Monitoring & Audit
Every conversation logged. Decision points auditable. Anomaly alerts included.
How We Work
From first call to measurable results
Use Case Scoping
We define the agent's exact scope, decision boundaries, tool access, and escalation rules before any build begins.
Prompt & Memory Design
We engineer the system prompt, design the memory layer, and define the retrieval strategy for knowledge-base agents.
Build & Red Team
We build the agent, then red-team it, testing edge cases, adversarial inputs, and out-of-scope requests to find failure modes before deployment.
Deploy & Monitor
We deploy to your environment with a monitoring dashboard showing every conversation, decision point, and tool call. Full handover and training included.
Types of AI Agents We Build
Four AI agent types our agency builds for production deployment
Every agent is scoped, tested, and monitored before going live. These are the deployments that consistently deliver measurable business outcomes.
Lead Qualification Agent
Monitors every inbound channel, web forms, email, live chat, and immediately evaluates leads against your ICP criteria using AI. Scores, routes, and responds within seconds, any time of day, without a human in the loop for tier-1 triage.
Real-world example
A B2B software company receives 80+ inbound enquiries per week. Their Tkist AI agent pre-qualifies each one, books discovery calls with ICP-matched leads directly into the sales calendar, and routes mismatched enquiries to a nurture sequence, without any rep involvement.
94% of leads pre-qualified. Response time: 47 seconds average. Reps only touch qualified leads.
Customer Support Agent
Trained on your product documentation, pricing, onboarding guides, and top 200 support tickets. Resolves tier-1 enquiries instantly. When a question falls outside its knowledge base, it escalates with a full conversation transcript and a recommended next action, not a blank handoff.
Real-world example
A SaaS company with 3,000 users reduced first-response time from 4 hours to 22 seconds. 73% of support tickets resolved without human intervention. CSAT scores increased from 3.8 to 4.9.
73% self-resolved. 22-second first response. CSAT from 3.8 to 4.9.
Internal Knowledge Agent
Connected to your internal documentation, Notion, Confluence, SharePoint, Slack history, and internal wikis. Any employee asks a question in natural language and receives a precise, sourced answer from your actual knowledge base instead of searching for 25 minutes or guessing.
Real-world example
A 200-person professional services firm deployed an internal agent across their HR policies, proposal library, and project methodology documentation. New-hire questions resolved in seconds. Senior consultant time spent on internal queries reduced by 60%.
60% reduction in internal queries to senior staff. Answers sourced from 47,000 internal documents.
Workflow Orchestration Agent
Monitors external events (emails, CRM updates, calendar events, payment notifications) and triggers multi-step business processes automatically. Not just a single API call, a multi-tool agent that reasons about what needs to happen next and executes the correct sequence.
Real-world example
A logistics company deploys an orchestration agent that watches for shipment exception emails, cross-references against customer SLAs, drafts and sends proactive customer notifications, creates internal escalation tasks, and updates the CRM, all without a human seeing the trigger email.
14 hours per week returned per operations manager. Zero missed SLA notification triggers.
The Conversion Gap
Five things that separate a production AI agent from a chatbot demo that fails in the real world
73%
of customer tier-1 enquiries resolved by a trained AI agent vs 18% by scripted chatbots
The gap between a scripted chatbot and a trained AI agent is structural, not incremental. A scripted bot can only answer questions it was built to expect. An AI agent understands intent, reads context, consults your knowledge base, asks clarifying questions, and handles the variations that no script writer anticipated. The resolution rate difference is measured in multiples.
21×
more likely to qualify a lead when the first response comes in under 5 minutes
An AI agent never sleeps, never has back-to-back calls, and never leaves a form submission unread until Monday. Every inbound lead receives a qualified response within seconds of arrival. The conversion impact of speed-to-lead improvement is one of the most reliable and measurable improvements available to any sales operation.
90%
lower cost per interaction for AI agents vs equivalent human handling at scale
A trained AI agent handling 500 tier-1 support enquiries per day costs a fraction of the equivalent human headcount, with no training time, no sick days, no knowledge gaps between shifts, and perfect consistency. The economics of AI agents are not marginal improvements on existing costs. They are structural changes.
34%
higher customer satisfaction scores where AI agents include proper escalation logic
Poor AI experiences fail because agents answer out-of-scope questions badly rather than handing off cleanly. Escalation logic is not a nice-to-have. It is the feature that determines whether the agent earns trust or destroys it. We design the human handoff path as carefully as the agent's core capabilities.
3 min
average lead qualification time with our agents vs a 4-hour industry average
Our lead qualification agents read inbound enquiry data, match it against your ICP criteria, ask follow-up questions, score the lead, and route it to the right person in under 3 minutes, any time of day. The commercial value is straightforward: you respond to every high-value lead before your competitors know it exists.
Client Result
Software / Technology, Enterprise Sales
AI agent pre-qualifies 94% of inbound leads. Cost per qualified lead cut by 88%.
Leads pre-qualified by AI
Before
0%
After
94%
Cost per qualified lead
Before
$180
After
$22
Out-of-hours response time
Before
Next day
After
Instant
We installed the agent on a Thursday evening. By Monday morning it had pre-qualified 34 leads and booked 8 demo calls. Our previous chatbot had not booked a single call in six months.
Ravi S.
Head of Growth
Mid-Market B2B SaaS Company
Want results like these for your business?
See all case studiesWhy Tkist
What you get with Tkist that you won't get anywhere else
| Feature | Tkist | Basic Chatbot (Drift / Intercom) | In-house IT Build |
|---|---|---|---|
| Trained on your actual product data | ✓ | ✗ script-based | varies |
| Multi-system tool use (CRM, calendar) | ✓ | ✗ | varies |
| Escalation logic engineered in | ✓ | basic | varies |
| Red-team tested before deployment | ✓ | ✗ | rarely |
| Monitoring dashboard included | ✓ | basic | extra build |
| Privacy / on-prem model option | ✓ | ✗ | possible |
| Lead qualification built in | ✓ | ✗ | extra build |
| Ongoing iteration and tuning | ✓ | self-managed | extra resource |
Tools and Technology
The software stack we use for your ai agents & gpt builds work
Industries We Serve
AI Agents & GPT Builds for key industries
From Our Portfolio
Recent ai agents & gpt builds work
Common Questions
Questions about ai agents & gpt builds
What is the difference between an AI chatbot and an AI agent?
What AI models do you use?
How do you prevent the agent from saying incorrect things?
Can the agent connect to our CRM, calendar, or other software?
How long does it take to build an AI agent?
What data do you need to train the agent?
Content last reviewed: April 2026
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Tell us which part of your sales or support operation you want to automate. We define the agent's exact scope, tool access, and expected deflection rate, and give you a fixed build cost before you commit to anything.