Custom AI Agents for Business
Autonomous agents powered by GPT-4o and Claude that handle sales, support, research, and operations — without human input.
Agent Use Cases We Build
If a task involves decisions, tools, and multiple steps — an agent can automate it.
Sales Agent
Processes inbound leads, asks qualifying questions, fills CRM with complete data, and schedules follow-ups automatically — 24/7.
Support Agent
Resolves customer issues autonomously — searches knowledge base, checks order status, processes returns, escalates only edge cases.
Analytics Agent
Pulls data from multiple sources, identifies trends, generates formatted reports, and pushes insights to Slack or email on schedule.
HR Screening Agent
Reads resumes, runs initial chat interviews, scores candidates against your criteria, and notifies hiring managers of top matches.
Content Agent
Writes posts, adapts tone per platform, generates ideas from a content plan, and schedules publications automatically.
Operations Agent
Coordinates tasks between teams, tracks deadlines, sends reminders, and generates progress reports without manual oversight.
Technology Stack
We use the most capable models and frameworks available — selected based on your cost, latency, and privacy requirements.
What Sets Our Agents Apart
Tool use: search, APIs, databases, CRM — real actions, not just text
Persistent memory across sessions via vector database
Structured output: agents return data in schemas your systems expect
Human-in-the-loop option for high-stakes decisions
Multi-agent orchestration for complex parallel workflows
Full observability: every reasoning step is logged and traceable
Cost controls: token budgets and rate limits per task
Incremental delivery — you test each capability before we extend
AI Agent Projects We Delivered
Autonomous agents running in production.
Lead qualification agent for a B2B SaaS — saved 15 hours per week
A B2B SaaS company was receiving 200+ inbound leads per week. Sales reps spent 15 hours qualifying them manually — asking the same 8 questions over email, waiting for responses, then updating CRM.
AI sales agent that automatically sends personalized qualification emails, interprets free-form replies using GPT-4o, fills CRM fields, scores leads by fit, and assigns hot leads to the right rep with a summary.
15 hours/week of manual work eliminated. Lead response time: from 8 hours to under 4 minutes. CRM data completeness improved from 40% to 96%.
Analytics reporting agent for a fintech — 6 hours to 4 minutes
The growth team at a fintech company spent 6 hours every Monday morning pulling data from 5 different sources (Mixpanel, Stripe, PostgreSQL, Google Ads, HubSpot) and assembling a weekly report.
Autonomous analytics agent that runs every Monday at 7AM: pulls data from all 5 sources, calculates KPIs, identifies anomalies, writes a narrative summary, and posts the formatted report to Slack.
Monday report time: 6 hours → 4 minutes. Report is ready before the team starts work. Analyst now focuses on interpretation, not data collection.
CV screening agent for a high-volume recruiter — 300 CVs in 40 minutes
A recruitment firm processing 300 CVs per week for 12 active job positions. Screeners spent 3 hours per position just doing first-pass filtering before any qualified review.
Multi-step agent pipeline: reads each CV, extracts structured data (experience, skills, education), scores against job requirements, flags red/green/yellow candidates, and generates a ranked shortlist with reasoning.
300 CVs screened in 40 minutes vs. 36 hours manually. Top-10 shortlist accuracy: 88% match with what senior recruiters would have selected. Time-to-first-interview cut by 5 days.
Pricing
Priced by scope of tools, integrations, and reasoning complexity.
Single-Task Agent
2–4 weeks
- ✓One focused task (e.g. lead qualification)
- ✓1–2 tool integrations
- ✓Basic memory (conversation context)
- ✓Telegram / Slack / API delivery
- ✓30-day post-launch support
Business Agent
6–10 weeks
- ✓Multi-step workflow automation
- ✓CRM, email, calendar integrations
- ✓Long-term memory with vector DB
- ✓Admin dashboard for monitoring
- ✓3 months of support included
Multi-Agent System
2–4 months
- ✓Multiple agents collaborating on tasks
- ✓Orchestrator + specialist agent architecture
- ✓Custom tool library and API gateway
- ✓Full observability and cost analytics
- ✓6 months of support included
How We Build AI Agents
Workflow Mapping
We document the exact task sequence, decision points, tools needed, and edge cases before writing a single line of code.
3–5 daysPrototype
A minimal working agent on the real data. You interact with it and give feedback before we build out the full system.
1–2 weeksBuild & Integrate
Full agent with all tools, memory, and integrations. Each integration is tested against real production data.
2–8 weeksMonitor & Tune
Post-launch monitoring dashboard, cost tracking, and regular fine-tuning based on real usage patterns.
OngoingWhat Our AI Agent Clients Say
“The sales qualification agent eliminated 15 hours of manual work per week for our team. Leads are now contacted in under 4 minutes instead of 8 hours. CRM is finally complete and accurate.”
“Our Monday analytics report used to take the entire morning. Now the agent produces it by 7AM before anyone logs in. The team now actually has time to act on the data instead of collecting it.”
“Screening 300 CVs per week was killing our team's time. The agent does it in 40 minutes and the shortlists it produces match what our senior recruiters would pick. Genuinely impressive.”
Frequently Asked Questions
What is an AI agent and how is it different from a chatbot?
A chatbot follows a pre-written script and can only respond to questions it was programmed for. An AI agent is autonomous — it can reason through multi-step tasks, use external tools (search, APIs, databases, CRM), execute actions, and adapt to any situation. A sales agent, for example, can receive a lead, look up company info, check CRM history, draft a personalized email, and schedule a follow-up — all without human input.
How much does AI agent development cost?
A basic single-purpose agent (one task, one integration) starts from $2,000. A business agent with multiple tools, memory, and CRM integration costs $4,000–$8,000. A multi-agent system where agents collaborate on complex workflows starts from $15,000. Pricing depends on number of tools integrated, complexity of reasoning chains, and backend infrastructure required.
What AI models do you use to build agents?
We use OpenAI GPT-4o, Anthropic Claude 4, and Gemini 2.5 as the reasoning backbone. For orchestration we use LangChain, LangGraph, and custom agent frameworks. For memory we implement vector databases (Pinecone, Weaviate) and PostgreSQL for persistent state. Model selection depends on your cost targets, latency requirements, and data privacy constraints.
What tasks can an AI agent automate?
AI agents excel at: lead qualification and CRM data entry, customer support with autonomous resolution, content creation and scheduling, data research and report generation, HR screening and interview scheduling, e-commerce order management, and multi-step API orchestration. If a task involves decision-making, tool use, and multiple steps — an agent can handle it.
How long does it take to build a custom AI agent?
A focused single-task agent takes 2–4 weeks. A full business agent with multiple tools, memory, and integrations takes 6–10 weeks. A multi-agent system takes 2–4 months. We start with a discovery phase to map out the exact workflow, tools needed, and edge cases — this saves time during development and ensures the agent does exactly what you need.
Ready to Automate with AI?
Describe your workflow and we'll tell you exactly what an agent can automate — free 30-minute scoping call.