AI agents that handle real work, with guardrails
An AI agent is worth building when it takes a task off someone's plate end to end: qualifying an inbound lead, triaging a support ticket, researching a prospect, drafting a proposal. We build agents connected to your data and tools, with rules about what they may do alone and when a person must approve.
- Lead qualification
- Support triage
- Research agents
- 4–8 weeks
- To a first agent in production
- Human-in-loop
- For consequential actions
- Logged
- Every action the agent takes
(The problem)
AI is easy to demo and hard to trust in production
A prototype that works on ten examples can fail on the eleventh. Without tests, limits and logs, nobody is comfortable letting it act on real customers or data.
We build agents for one well-defined task at a time, test them on real past cases and keep a person in the loop for anything that matters.
What's included
Useful automation, not a demo.
- 01
Lead qualification
Inbound enquiries researched, scored and routed.
- 02
Support triage
Tickets classified, answered or escalated with context.
- 03
Research agents
Prospect and market research compiled into briefs.
- 04
Document drafting
Proposals, summaries and reports drafted for review.
- 05
Tool integrations
CRM, helpdesk, email, calendar and internal APIs.
- 06
Guardrails & logs
Approval steps, limits and full activity logs.
How it works
- 01
Pick the task
One task with clear inputs, outputs and a way to measure success.
- 02
Connect
Access to the data and tools the agent needs, and nothing more.
- 03
Test
Run against real past cases, with guardrails and approval steps added.
- 04
Deploy and expand
Live with monitoring and logs, then new responsibilities added step by step.
Mid-Market B2B SaaS Company · Software / Technology, Enterprise Sales
AI agent pre-qualifies 94% of inbound leads. Cost per qualified lead cut by 88%.
- Leads pre-qualified by AI
- Before0%
- After94%
- Cost per qualified lead
- Before$180
- After$22
- Out-of-hours response time
- BeforeNext day
- AfterInstant
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.
Tecklogist vs the alternatives
| Feature | Tecklogist | 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 we use
- GPT-4o
- Claude 3.5 Sonnet
- LangChain
- Pinecone
- n8n
- Twilio
- Intercom API
- HubSpot CRM
Industries we serve
- Legal
- Healthcare
- E-commerce
- Finance
- Real Estate
- SaaS
- Professional Services
- Logistics
Good questions
Last reviewed October 2026
What's the difference between an agent and a chatbot?+
A chatbot answers questions. An agent takes actions, such as updating records, sending emails or creating tickets, as part of a task.
Which AI models do you use?+
OpenAI, Anthropic Claude and open-source models, chosen for the task, cost and data requirements.
How do you stop it making mistakes?+
Narrow permissions, testing on real past cases, confidence thresholds and human approval for anything consequential.
Is our data used to train models?+
We use business API terms that exclude training on your data, and can use private or self-hosted models where required.
How do we know it's working?+
Every action is logged and we report on accuracy, time saved and escalations.
What does it cost?+
A first agent for one task is a fixed project fee, plus model usage costs that depend on volume.
Get a free ai agents & gpt builds proposal
Tell us about the project and we'll send a tailored proposal within one working day, with no commitment.