Leads and sales
Capture requests, validate data, qualify the need and give the responsible person full context.
AI automation agency for real business workflows
Rollder builds custom AI agents and workflow automation for lead handling, support, documents and data movement — connected to your CRM, APIs and existing systems.
One controlled workflow
AI agent for inbound requestsRequest
Qualify
CRM
Owner
Automate the work, not add another isolated tool
We start with data, decisions and ownership. AI is added only where it provides a useful capability.
Describe your workflow →Customer support
Find answers in approved sources and transfer complex or sensitive questions to a person.
Documents and knowledge
Find facts, structure material, prepare drafts and preserve sources for review.
Internal operations
Synchronize CRM, APIs, spreadsheets and portals without manual copying or invisible failures.
Three ways to remove manual work
AI agents are the primary focus. Automation, integrations and web systems create the reliable operational layer around them.
Custom AI agents for business
We build AI agents that use approved knowledge, execute permitted actions, hand uncertain cases to people and keep an inspectable decision trail.
Explore the solution ↗Automation and integrations
We remove manual handoffs between forms, CRM, email, Telegram, spreadsheets and internal services while keeping exceptions under control.
Explore the solution ↗Custom web systems
We build internal portals, customer workspaces and web products as an operational part of automation, not as an isolated decorative website.
Explore the solution ↗Focused solutions
Start with the workflow that is already costing the team
Commercial pages for common operational bottlenecks, with explicit boundaries, deliverables and human approval.
Explore all solutions →AI automation for marketing agencies
We connect lead intake, scoping, delivery and reporting so an agency can grow without adding another layer of manual coordination.
Explore →AI lead qualification automation
Turn fragmented inbound requests into structured, reviewable opportunities with source attribution, duplicate checks, fit reasoning and a responsible owner.
Explore →Custom CRM automation services
We connect lead sources, qualification, ownership and follow-up so CRM status reflects real work instead of becoming another manual reporting task.
Explore →Real systems without invented metrics
Names and data are withheld. We show the problem, boundaries, architecture and delivered capability.
All case studies →AI consultant for a vitamin catalogue
Customers needed clear explanations of the catalogue, usage guidance and differences between products. The team wanted to automate repetitive consultations without turning the system into a source of diagnoses or personalized medical advice.
Open case study ↗AI tools for prediction-market analysis
The team needed a controlled way to collect market signals, compare prices with scenario estimates and apply consistent evaluation rules across a large number of events.
Open case study ↗CI/CD and a shared stack for a marketing team
Several departments supported client projects, while information about releases, environments, access and delivery status was distributed across different tools and people.
Open case study ↗From a focused validation to a production system
The range is refined around the problem, data and integrations. Each phase has its own outcome and does not force a larger engagement.
$0–300
Define the problem, data, exceptions, risks and the shortest useful validation.
$500–1,500
Implement one priority scenario using controlled data.
from $2,000
Connect production systems, monitoring, documentation and handover.
AI should not turn the workflow into a black box
We design systems so the team understands the boundaries, sees failures and can keep operating without depending on one vendor.
People stay in the loop
Sensitive and uncertain decisions have an explicit review or approval path.
Actions remain explainable
Sources, rules, status and escalation reasons stay visible instead of hiding behind magic.
The system handles failure
Logs, retries, alerts and a manual fallback are designed into the workflow.
Code and context are handed over
Access, documentation, CI/CD and ongoing ownership are made explicit.
Decisions to make before development
Practical guidance on cost, AI boundaries and process audits, based on direct engineering decisions.
All insights →Where a marketing agency should start with AI automation
Prioritize agency workflows by frequency, delay, error cost and ownership instead of automating the most visible task first.
Read →How to design AI lead qualification without losing control
A reliable qualification system combines deterministic exclusions, explainable AI analysis, CRM context and manual approval.
Read →How to evaluate an AI customer support system before launch
Test grounded answers, policy boundaries, escalation and operational failure before allowing AI into a customer support workflow.
Read →Questions before starting
Do we actually need an AI agent?
Not always. If a deterministic automation or integration is more reliable, we recommend the simpler approach.
How can we start with a limited budget?
Start with one process diagnosis or one working scenario. This validates data, boundaries and usefulness before a wider implementation.
Can you integrate our CRM and APIs?
Yes, when the system offers an API, webhook or another controlled data exchange method. Integration risks are identified before development.
Can we discuss the project under NDA?
Yes. Before receiving confidential details, we agree on access and data-handling rules.
Have a workflow that needs AI or automation?
Describe the workflow in a few sentences. We will identify the data and integrations that need validation before an estimate.
✓No confidential details in the first request✓NDA before access to internal data✓Start with the smallest testable phase