Agentic AI
Custom autonomous AI agents built with production-grade frameworks (LangGraph, Autogen) that can make decisions, run API workflows, and handle complex multi-step tasks independently.
What you get
- Stateful decision graphs and loop controls
- Tool-use orchestration and multi-agent collaboration
- Human-in-the-loop validation dashboards for supervisor sign-offs
- Observer trace logging and fail-safe recovery paths
How we deliver.
A structured engagement from discovery to deployment — no surprises, no scope fog.
Agent system architecture
We design the decision graphs, loop controls, state schemas, and memory architecture for the system.
Tool & API wiring
We build robust schemas and connect the agent safely to your APIs, database, and third-party platforms.
Supervisor & human-in-the-loop loops
We configure verification thresholds and build simple approval views for high-risk operations.
Testing & agent evals
We build simulator testbeds to benchmark agent behaviors, verify loops terminate, and control costs.
Deployment & trace auditing
We deploy with LangSmith or Phoenix monitoring to trace every tool call, decision path, and token expense.
Where this applies.
Autonomous operations agents
Agents that handle customer onboarding, background verification, document assembly, and pipeline updates.
Automated support supervisors
Multi-agent systems where support agents propose solutions and supervisor agents verify before sending.
Data extraction & analysis agents
Agents that search web portals, scrape data, extract details, compile reports, and post findings.
Automated dev & DevOps agents
Self-correcting agents that run code, parse compilation errors, run tests, and commit fixes.
Technical depth.
Stateful graph orchestration
Built on directed acyclic graphs (DAGs) using LangGraph to allow complex loops and conditional routing.
Long-term & short-term memory
Keeps session history in vector databases and persistent database stores for contextual awareness.
Strict tool schema validation
Every tool call is validated against OpenAPI schemas or strict Zod/Pydantic schemas.
Token & cost budget guardrails
Built-in agent rate-limits and token/cost ceilings to prevent runaway infinite loops.
Common questions.
Q.How do you prevent agents from running wild?
We enforce hard loop-count limits, maximum per-run token budgets, and implement Human-in-the-loop controls for sensitive actions like sending emails or payments.
Q.What frameworks do you use?
We primarily build stateful agents using LangGraph and Autogen with Python/FastAPI, utilizing LangSmith for full trace auditing and observability.
Q.Can agents learn from their mistakes?
Yes, we implement reflection loops where agents analyze their own outputs, compare them to criteria, and automatically correct errors before returning a result.
Q.How are multi-agent systems structured?
We design hierarchies where a coordinator agent delegates tasks to specialized sub-agents (e.g., researcher, writer, validator), compiling and verifying the final output.
Featured projects.
AI infrastructure cleanup: cost & reliability overhaul
A production AI system that was slow, over-budget, and failing silently — audited, root-caused, and rebuilt into something dependable.
Chrome Extension for automated CRM lead extraction
A Manifest V3 browser extension that lets sales representatives clip prospect contacts from web directories directly into their CRM with a single click.
Cross-platform mobile app for real-time logistics tracking
A high-performance React Native / Expo app that lets field operators track inventory and log tasks in real time, even while offline.
What our partners say.
“Our staff spent hours searching files, and our early AI bot just hallucinated answers. Lesscode rebuilt our RAG pipeline with precision embedding and citations. Accuracy went to 99%, and data leaks are zero. Stellar work.”
“The AI voice receptionist Lesscode built qualified and booked over 230 jobs in our first month. We no longer miss calls after hours, and GHL scheduling syncs perfectly. Highly recommended.”
“Our AI token costs were out of control and queries were failing silently in production. Lesscode did an audit, diagnosed three critical bottlenecks, and completed the refactor. Costs dropped by 63% and response times are now sub-second.”
“Their workflow automations connected our CRM, billing, and reporting tools via n8n and Python scripts. What used to take hours of manual copy-pasting is now fully hands-off and bulletproof.”
Building something ambitious, or fixing something that's gone sideways?
Tell us where you are and where you're trying to get to. We'll tell you honestly whether — and how — we can help.