Custom AI Agent Development
Stop paying humans to do work AI agents can handle. Build autonomous agents that integrate with your tools, execute multi-step workflows, and take real actions, with full observability and safety controls. Production-ready in 4-8 weeks.
14+
Years of Experience
800+
Projects Delivered
100+
Engineers
4.9★
Clutch Rating
Your team spends 30-50% of their time on tasks that follow a pattern: checking systems, pulling data, making decisions based on rules, updating records, and sending notifications. These are not creative tasks. They are process tasks, and they are exactly what AI agents are built to handle.
500+
Onboarding apps processed overnight
An agent can collect info, verify documents, create accounts, and trigger workflows across your systems while your team sleeps.
1,000+
Leads researched and enriched per day
An agent monitors new leads, researches companies, scores prospects against your ICP, and updates your CRM automatically.
50-70%
Faster incident resolution
An agent monitors infrastructure, diagnoses issues, and executes runbook procedures before your engineers get paged.
An AI agent is not a chatbot. It does not wait for someone to ask it a question. It monitors triggers, reasons through multi-step workflows, calls your APIs, reads and writes to your databases, and takes real actions in your systems.
We build production-grade AI agents using LangGraph, CrewAI, and the Model Context Protocol (MCP), deployed to your infrastructure with full observability, human-in-the-loop safety controls, and enterprise-grade reliability.
Every decision is traceable. Every action is logged. Every edge case has a fallback.
Why Chatbots and Simple Automation Are Not Enough
Your team has tried chatbots for answering questions and Zapier for automating workflows. Both hit a wall when tasks require judgment, context, and multi-step reasoning.
Chatbots answer questions but cannot take action
A chatbot can tell a customer their order status. It cannot process a return, update your inventory system, issue a refund through Stripe, and notify the warehouse. Actions that span multiple systems require an agent, not a chatbot.
Zapier breaks when workflows need judgment
Rule-based automation follows rigid "if X then Y" logic. The moment a workflow encounters ambiguous data, an edge case, or a decision that requires context, it fails silently or routes everything to a human queue. You end up babysitting your automations instead of trusting them.
Your team wastes hours on process work that follows patterns
Lead qualification, data entry, document processing, compliance checks, report generation: these tasks follow predictable patterns but require enough judgment that simple automation cannot handle them. Your skilled employees spend 30-50% of their time on work an AI agent could do faster, more consistently, and around the clock.
No visibility into what your automation is actually doing
When a Zapier workflow fails at step 7 of 12, you get a cryptic error log. When an employee makes a mistake in a manual process, you may not find out for weeks. Without observability into every decision and action, you are operating blind and fixing problems after they cause damage.
The cost of manual processes: A team of 5 people spending 30% of their time on process work at $80,000/year each costs $120,000 annually in lost productivity. That work does not scale. Every new customer, every new transaction adds more manual load.
The solution: A custom AI agent that integrates with your existing tools, reasons through multi-step workflows, handles edge cases intelligently, and takes real actions in your systems. Every decision is traceable. Every action is logged. Your team focuses on work that requires creativity, strategy, and human judgment while the agent handles the rest.
What Is Custom AI Agent Development?
Custom AI agent development is the process of building an autonomous software system that uses large language models (LLMs) to reason through complex tasks, make decisions, and take real actions in your business systems. Unlike chatbots that respond to questions with text, AI agents integrate with your tools (APIs, databases, CRMs, SaaS platforms) and execute multi-step workflows end to end: reading data, making context-aware decisions, calling APIs, updating records, sending communications, and handling exceptions.
At Salt Technologies AI, we build production-grade AI agents using frameworks like LangGraph (for complex stateful workflows with branching and cycles), CrewAI (for multi-agent collaboration), and the Model Context Protocol (MCP) for standardized tool integration. Every agent includes an orchestration engine that manages multi-step reasoning, persistent memory for context across executions, and a comprehensive observability layer that traces every decision and action. We deploy agents on your infrastructure with human-in-the-loop safety controls, budget limits, rate controls, and scope constraints.
AI agents are the next evolution beyond chatbots and workflow automation. A chatbot tells you the status. An agent changes the status. A Zapier workflow follows rigid rules. An agent reasons through ambiguity. The result is work that gets done faster, more consistently, and around the clock without scaling your headcount.
70-80%
Reduction in Manual Processing
24/7
Autonomous Operation
4-8 Weeks
From Kickoff to Production
100%
Decision Traceability
AI Agent vs. Chatbot vs. Workflow Automation
Understanding which AI solution fits your workflow is the difference between a tool that helps and a tool that transforms.
| Capability | Chatbot | Zapier / Make | AI Agent |
|---|---|---|---|
| Answers questions | |||
| Takes real actions in systems | |||
| Handles ambiguity and edge cases | |||
| Multi-step reasoning | |||
| Integrates with 5+ tools | Limited | ||
| Context-aware decisions | Basic | ||
| Full decision traceability | Logs only | ||
| Human-in-the-loop safety |
AI agents combine the intelligence of chatbots with the action-taking capability of workflow automation, plus the reasoning to handle edge cases neither can.
Discuss Your WorkflowThe ROI of a Custom AI Agent
A $20,000 agent that automates 70% of a manual workflow typically pays for itself in 2-4 months. Here is the math.
Example: 5-person team spending 30% of time on process work
Before: Manual Process Work
After: AI Agent (70% Automation)
$78,000
Saved per year
3.9x
Return on investment (Year 1)
~3 Months
Payback period
Based on 5 team members at $80K fully loaded cost, 30% time on process work, 70% automation rate, and $500/month API and infrastructure costs. Actual results depend on workflow complexity, volume, and team size. Most clients see positive ROI within 2-4 months.
We will estimate your specific ROI on the discovery call.
Is Custom AI Agent Development Right for You?
AI agents deliver the highest ROI for workflows that require judgment, span multiple systems, and follow patterns your team repeats hundreds of times.
- You need AI that takes actions, not just generates text or answers questions
- You want to automate complex, multi-step workflows that span multiple systems and tools
- You need an agent that integrates with your existing tools: CRMs, databases, APIs, SaaS platforms
- You want full observability and traceability for every decision the AI makes
- You need human-in-the-loop controls for high-stakes actions (approvals, budget limits, escalation)
- You have outgrown simple automation tools like Zapier or Make and need intelligent, context-aware automation
If two or more sound like you, let's talk.
Book a Free Discovery CallAI Agent Development Use Cases
See how businesses use custom AI agents to automate complex workflows, reduce manual processing, and scale operations without scaling headcount.
Automated Customer Onboarding Agent
An AI agent that collects customer information, verifies documents against compliance rules, creates accounts across your systems (CRM, billing, project management), sends personalized welcome sequences, triggers setup workflows, and escalates edge cases to human operators. Companies using onboarding agents report 70-80% reduction in manual processing time and 3x faster time-to-activation for new customers.
Sales Pipeline Automation Agent
An agent that monitors new leads, researches companies using public data and enrichment APIs, scores and qualifies prospects against your ICP, drafts personalized outreach messages, schedules meetings, updates CRM deal stages, and alerts sales reps only for high-value opportunities that need human touch. Sales teams using AI agents report 40-60% more qualified meetings per rep per month.
DevOps and Infrastructure Agent
An AI agent that monitors your infrastructure (AWS, GCP, Azure), detects anomalies and performance degradation, diagnoses root causes by querying logs and metrics, executes automated runbooks (scaling resources, restarting services, clearing caches), and escalates to on-call engineers only when human judgment is required. Reduces mean time to resolution (MTTR) by 50-70%.
Multi-System Data Processing Agent
An agent that extracts data from multiple sources (APIs, databases, file uploads, emails), validates and transforms it according to your business rules, routes processed data to the correct downstream systems, handles exceptions with intelligent fallback logic, and generates reconciliation reports. Eliminates manual data entry and cross-system synchronization work.
Financial Operations Agent
An AI agent that processes invoices, matches purchase orders, reconciles transactions across accounting systems, flags anomalies for review, generates financial reports, and routes approval requests to the right stakeholders based on amount thresholds and department rules. Finance teams report 60-80% reduction in manual reconciliation time.
Compliance and Audit Agent
An agent that continuously monitors your systems for compliance violations, checks transactions against regulatory rules (KYC, AML, HIPAA, SOC2), generates audit trails, prepares compliance reports, and alerts compliance officers when manual review is required. Reduces compliance review time by 50-70% while improving coverage.
Content Operations Agent
An AI agent that monitors content requests, generates drafts using your brand guidelines and style guides, routes content through approval workflows, publishes to your CMS and social channels on schedule, and tracks performance metrics. Content teams using AI agents produce 3-5x more output without increasing headcount.
Customer Support Escalation Agent
An agent that triages incoming support tickets, gathers diagnostic information by querying your systems, attempts automated resolution for known issues, prepares detailed context summaries for tickets that need human attention, and routes escalations to the right specialist based on issue type, severity, and customer tier. Reduces average resolution time by 40-60%.
See your workflow in this list? Let's talk about automating it.
Book a Free Discovery CallWhat's Included in Your AI Agent Build
Eight deliverables. Production-ready from day one. Everything you need to deploy, monitor, and operate your AI agent.
Production-Ready AI Agent
A fully functional AI agent deployed to your infrastructure, running 24/7 with health monitoring, automatic restarts, and graceful error handling. Built with enterprise-grade reliability for real business workflows.
Tool and API Integration Layer
Connections to your CRM (Salesforce, HubSpot), databases (PostgreSQL, MongoDB), communication tools (Slack, email), project management (Jira, Linear), cloud services, and any system with an API. The agent reads from and writes to your actual systems.
Multi-Step Orchestration Engine
The reasoning core that drives your agent: multi-step workflows with branching logic, conditional execution, error handling, automatic retries with exponential backoff, and state management across long-running processes.
Observability Dashboard
Trace every decision, tool call, and action in real-time. See full reasoning chains for every workflow execution. Replay past runs for debugging. Set alerts for failures, anomalies, and cost thresholds. Accessible to non-technical team members.
Human-in-the-Loop Guardrails
Approval workflows for high-stakes actions. Budget limits per execution. Rate controls to prevent runaway loops. Scope constraints that restrict the agent to approved tools and data. Confidence thresholds that trigger automatic escalation.
Memory and Context Management
Persistent state management so the agent remembers context across conversations and workflow executions. Long-term memory for learning from past interactions. Short-term working memory for complex multi-step reasoning within a single execution.
Testing Suite and Performance Benchmarks
Comprehensive test coverage: happy path scenarios, edge cases, failure modes, concurrent execution, and rate limit handling. Performance benchmarks documenting throughput, latency, accuracy, and cost per execution. Regression test suite for ongoing maintenance.
Documentation, Runbook, and Team Training
Complete documentation covering architecture, tool integrations, workflow logic, observability dashboard usage, and troubleshooting. Operational runbook for common scenarios. Hands-on training for your team to operate and maintain the agent independently.
How Custom AI Agent Development Works
Workflow Mapping
3-5 daysDocument the end-to-end process the agent will automate. Map every trigger, decision point, action, and edge case. Define success criteria and measurable KPIs. Identify which actions require human approval and which can be fully autonomous.
Agent Architecture Design
3-5 daysDesign the agent architecture: tool integrations, decision trees, state management, memory systems, safety controls, and fallback behaviors. Select the optimal framework (LangGraph for complex stateful workflows, CrewAI for multi-agent collaboration, or custom orchestration). Define observability requirements and approval workflows.
Build Sprint
2-4 weeksDevelop the agent, build tool integrations, implement orchestration logic, and test with real scenarios from your workflow. Iterate on decision quality, tool reliability, and edge case handling. Build the observability dashboard and admin controls.
Stress Testing and Safety Validation
1 weekTest edge cases, failure modes, concurrent execution, rate limit handling, and human-in-the-loop workflows. Validate that guardrails prevent unintended actions. Benchmark performance: throughput, latency, accuracy, and cost per execution. Document all failure modes and recovery procedures.
Production Deployment and Monitoring
2-3 daysDeploy to your infrastructure with production-grade monitoring, alerting, and automatic recovery. Configure dashboards for workflow tracking, error rates, and performance metrics. Train your team on the observability dashboard, runbook procedures, and ongoing maintenance. Run in shadow mode before going fully autonomous.
Like the process? Get a free workflow mapping session for your use case.
Get a Free QuoteAI Agent Architectures We Build
We select the right architecture based on your workflow complexity, not a one-size-fits-all approach.
Single Agent
One agent handles an end-to-end workflow with multiple tools. Best for well-defined processes with clear decision logic: customer onboarding, invoice processing, lead qualification.
Starting at
$20,000
Multi-Agent System
Specialized agents collaborate: one researches, another analyzes, a third executes, a fourth reviews. Best for complex workflows that span departments or require different expertise at each step.
Starting at
$35,000
Supervisor Architecture
A supervisor agent orchestrates worker agents, allocates tasks dynamically, and handles escalation. Best for high-volume workflows that need parallel processing and load balancing.
Starting at
$40,000
Not sure which architecture fits? Our workflow mapping phase (included in every engagement) identifies the optimal approach.
Get a Recommendation for Your Use CaseAI Agent Development: Pricing and Timeline
Timeline
4-8 weeks
Starting At
$20,000
What Affects AI Agent Development Cost
- Number of tools, APIs, and systems the agent integrates with (2-3 tools vs. 8-10 tools)
- Complexity of decision logic, branching workflows, and exception handling
- Single-agent vs. multi-agent architecture (collaborative agent systems cost more)
- Compliance and safety requirements (financial, healthcare, or regulatory workflows)
- Whether custom model training or fine-tuning is needed for domain-specific decisions
- Volume of transactions and concurrency requirements (hundreds vs. thousands per day)
Get a fixed quote for your AI agent project
Tell us about your workflow. We map the process, design the agent architecture, and give you an exact price and timeline before any build work begins.
Book a Free ConsultationAI Agent Development by Industry
Every industry has workflows that AI agents can automate. We adapt agent architecture, tool integrations, and compliance controls to your sector.
AI Agents for SaaS Companies
Automated customer onboarding, usage monitoring and churn prevention agents, trial-to-paid conversion workflows, support ticket triage and resolution, and product-led growth automation. Integrate with your existing SaaS stack (Stripe, Intercom, Segment, HubSpot).
Learn more about AI for SaaSAI Agents for Fintech
Transaction processing and reconciliation agents, KYC/AML compliance monitoring, fraud detection workflows, automated financial reporting, and regulatory filing automation. SOC2 and PCI-DSS compliant architecture with full audit trails.
Learn more about AI for FintechAI Agents for Healthcare
Patient intake and scheduling automation, claims processing agents, clinical workflow coordination, prior authorization automation, and compliance monitoring. HIPAA-compliant architecture with PHI-safe data handling and audit logging.
Learn more about AI for HealthcareAI Agents for E-commerce
Order processing and fulfillment agents, inventory management automation, returns and refund processing, customer service escalation workflows, and supplier coordination. Integrate with Shopify, WooCommerce, and custom platforms.
Learn more about AI for E-commerceDifferent industry? We build AI agents for any sector with repeatable workflows and system integrations.
Tell Us About Your IndustryAI Agent Development Technology Stack
We select the optimal technology stack for your agent based on workflow complexity, integration requirements, performance needs, and compliance constraints. Our standard stack includes the most mature and production-tested AI agent frameworks available.
Why Choose Salt Technologies AI for Agent Development
Building a demo agent takes a weekend. Building a production agent that your business depends on takes engineering discipline. Here is what makes our approach different.
Safety-First Agent Design
Every agent includes human-in-the-loop approvals for high-stakes actions, budget limits per execution, rate controls to prevent runaway loops, scope constraints that restrict agent actions to approved domains, and confidence thresholds that trigger escalation. We do not ship agents that can cause uncontrolled damage.
Full Observability and Traceability
Our observability dashboard traces every decision, tool call, reasoning step, and action the agent takes. You can audit any workflow from trigger to completion, see the full reasoning chain for every decision, and replay executions for debugging. Every action is logged with timestamps, inputs, outputs, and latency.
Battle-Tested Orchestration Frameworks
We build agents using production-grade frameworks: LangGraph for complex stateful workflows with branching and cycles, CrewAI for multi-agent collaboration, and MCP (Model Context Protocol) for standardized tool integration. These are not fragile prompt chains. Agents handle errors, retries, timeouts, and concurrent execution gracefully.
Designed for Production, Not Demos
Our agents run 24/7 with monitoring, alerting, automatic recovery, and graceful degradation. We implement circuit breakers, retry logic with exponential backoff, dead letter queues for failed executions, and shadow mode for safe rollout. This is not a hackathon project. It is infrastructure your business depends on.
Multi-Agent Expertise
We design and build multi-agent systems where specialized agents collaborate: one agent researches, another analyzes, a third executes, and a fourth reviews. Orchestration frameworks coordinate handoffs, shared memory, and conflict resolution between agents. This is how complex business workflows get automated end to end.
Backed by 14+ Years and 800+ Projects
Salt Technologies AI is the AI division of Salt Technologies, with over 14 years of software engineering experience, 800+ projects delivered across industries, 100+ engineers, and a 4.9 Clutch rating. ISO 9001:2015 and ISO 27001:2022 certified. Our agent development is grounded in enterprise software engineering discipline, not AI hype.
14+
Years of Experience
800+
Projects Delivered
100+
Engineers
4.9★
Clutch Rating
AI Agent Development: Frequently Asked Questions
How much does custom AI agent development cost?
What is the difference between a chatbot and an AI agent?
How do you ensure the AI agent does not make mistakes or cause damage?
What tools and systems can an AI agent integrate with?
Can you build multi-agent systems where multiple agents collaborate?
How long does it take to build a custom AI agent?
Can I see what the AI agent is doing in real-time?
What happens when the agent encounters a situation it cannot handle?
What is the difference between an AI agent and workflow automation like Zapier?
What frameworks do you use to build AI agents?
How do you handle AI agent costs and API usage at scale?
Can an AI agent run continuously or does it only run on demand?
What industries do you build AI agents for?
Do we own the AI agent code and intellectual property?
How is your AI agent development different from hiring AI freelancers?
What happens after the AI agent is deployed? Do you offer ongoing support?
Choose Your Starting Point
Most clients go straight to the AI Agent Build. But if you want to validate feasibility first or need broader AI guidance, we have entry points for that.
AI Readiness Audit
Get a prioritized AI roadmap for your business first. We identify which workflows are best suited for AI agents vs. chatbots vs. automation.
Custom AI Agent Build
Go straight to production. Custom agent integrated with your tools, deployed with full observability and safety controls in 4-8 weeks.
AI Managed Pod
Ongoing improvements: new tool integrations, additional agents, expanded workflows, accuracy tuning, and continuous iteration based on production data.
Want to test feasibility first? Our AI PoC Sprint ($8,000) builds a working agent prototype with your real data so you can validate before committing to production.
No obligation to continue after any step. You own every deliverable.
View All AI ServicesGetting Started Is Simple
No lengthy procurement process. No upfront commitment.
Book a Free Call
30-minute discovery call. Tell us about the workflow you want to automate, the tools involved, and the outcomes you need. No sales pitch, no pressure.
Get a Fixed Quote
We map your workflow, design the agent architecture, and give you an exact price and timeline. No hourly billing. No surprises. You approve before we start.
We Build and Deploy
Work begins immediately. You see progress with regular demos. In 4-8 weeks, your AI agent is live, monitored, and handling real workflows autonomously.
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Every Week Your Team Spends on Manual Process Work Is Money and Time You Cannot Get Back
A $20,000 AI agent that automates 70-80% of a manual workflow pays for itself in 2-4 months. After that, every month is pure savings and scale. Book a free 30-minute call and we will map your highest-ROI automation opportunity.