AI Agent Development
Custom AI Agent Development
We build AI agents that take multi-step actions through your existing tools — not single-turn chatbots. Support agents, sales research agents, and voice agents, engineered with the guardrails and human-in-the-loop checkpoints that production use requires.
What ai agent development
An AI agent is a system that can plan a sequence of steps, call tools or APIs, and act on the results, rather than answering a single question and stopping. Algorimsoft designs and builds these agents around a specific business workflow — with explicit permissions, logging, and points where a human reviews or approves the agent's action.
Business problems this solves
- Support or sales teams repeat the same multi-step research and response process for every ticket or lead
- A workflow requires combining information from several systems before a decision can be made
- Existing automation (rule-based workflows) breaks whenever a request doesn't fit the exact expected pattern
- Teams want the benefits of automation without losing human oversight on consequential actions
- Phone or voice-based intake (reception, scheduling, triage) consumes staff time that could go to higher-value work
Capabilities
Tool-using agents
Agents that call your APIs, CRM, or internal tools as part of completing a task, not just generating text.
Multi-step workflow agents
Agents that plan and execute a sequence of steps — research, draft, verify, act — for a defined objective.
Support & sales agents
Agents that triage tickets, draft responses, qualify leads, or summarize accounts from CRM and ticket data.
Research agents
Agents that gather and synthesize information across documents, the web, or internal systems for a specific question.
Voice agents
Voice-driven agents for reception, intake, scheduling, or triage — connected to real calendars and business systems.
Human-in-the-loop workflows
Explicit approval steps and escalation paths for actions that shouldn't run fully autonomously.
How we build it
- 01
Workflow mapping
Document the exact steps, tools, and decision points a human currently uses to complete the task.
- 02
Tool & permission design
Define exactly which systems the agent can read from and act on, and where it must stop and ask.
- 03
Build & test
Build the agent against real (or realistic) inputs, including edge cases and failure modes.
- 04
Human-in-the-loop rollout
Launch with human review on agent actions, then narrow the review scope as confidence builds.
- 05
Monitor & iterate
Track agent decisions and outcomes in production and adjust tool access, prompts, or guardrails.
Technologies
- LangGraph & LangChain
- OpenAI, Anthropic & Google Gemini APIs
- Function calling / structured tool use
- Voice: telephony APIs & speech-to-text/text-to-speech pipelines
- n8n / Make for surrounding workflow orchestration
Use cases
- — An AI receptionist that answers calls, checks availability, and books appointments
- — A sales agent that researches a new lead, drafts outreach, and updates the CRM
- — A support agent that triages incoming tickets and drafts first-response replies for review
- — An internal research agent that answers questions across scattered internal documents
Industries served
Why Algorimsoft
- — Agents are designed around explicit tool permissions and human checkpoints, not unrestricted autonomy
- — Every agent workflow starts from mapping the real human process, not a generic "AI agent" template
- — The team building the agent also built the underlying AI development and automation stack it runs on
Engagement options
Single-workflow agent
One agent built and shipped for a specific, well-scoped workflow.
Voice agent build
An AI receptionist or intake agent connected to your calendar, CRM, and phone system.
Embedded AI engineer
Ongoing agent development as part of your product or operations roadmap.
Frequently asked questions
Ready to talk about ai agent development?
Tell us about your product, timeline, and team, and we'll follow up with next steps.