Agentic Systems

From Chatbots to
Digital Workers.

We engineer autonomous agents that don't just talk—they act. Plan, reason, tool-use, and execute complex workflows with human-level reliability.

Reasoning Engines

Standard LLMs are probabilistic word predictors. Agentic AI adds a "System 2" reasoning layer. Our agents use techniques like Chain-of-Thought (CoT) and ReACT loops to break down complex goals into executable steps.

Before taking any action, the agent plans its approach, critiques its own plan, and adjusts based on feedback. This reduces error rates and prevents "hallucinated actions."

ReACT Patterns
Self-Correction Loops
Goal Decomposition
Dynamic Planning

Secure Tool Execution

An agent without tools is just a philosopher. We give agents hands. By connecting them to your APIs, databases, and internal systems via secure function calling interfaces, we enable them to do real work.

From querying a SQL database to creating a ticket in JIRA or sending a transactional email, our agents interact with your infrastructure using authenticated, audit-logged tooling.

OpenAPI/Swagger Integration
SQL/Vector Database Access
Browser Automation (Headless)
Custom API Connectors

Multi-Agent Swarms

Complex problems require diverse skills. We architect "crews" of specialized agents—a Researcher, a Writer, a Coder, and a Reviewer—that collaborate to solve problems no single model can handle.

Using hierarchical or mesh orchestration patterns, these agents pass messages, share context, and hand off tasks to the most qualified specialist in the swarm.

Role-Based Specialization
Shared Memory Architectures
Hierarchical Task Delegation
Conflict Resolution protocols

The Agentic Stack

Agents require more than just inference. They need memory, state, and runtime environments.

State Management

Persistent graph storage (LangGraph) to track agent state, allowing for pause, resume, and "time travel" debugging.

Long-Term Memory

Vector-backed episodic memory allows agents to learn from past interactions and improve over time.

Evals & Observability

Tracing agent thought trajectories (LangSmith) to identify loops, stalls, and suboptimal reasoning paths.

Autonomy with Oversight

Enterprise agents cannot run wild. We implement "Human-in-the-Loop" (HITL) checkpoints for high-stakes actions.

  • Approval Workflows for Critical Actions
  • Real-time Intervention & Steering
  • Audit Trails of All Agent Decisions
  • Role-Based Access Control (RBAC) for Agents

The "Kill Switch"

Every agent we deploy comes with a hard-coded supervisory layer. If an agent deviates from its parameters or enters a loop, the supervisor terminates the thread instantly.

We Build Agents That Finish the Job

Deterministic Tooling

We strictly type our tool definitions. Agents don't guess JSON schemas; they strictly adhere to API contracts.

Cognitive Architectures

We don't just prompt; we engineer memory, planning, and reflection modules inspired by cognitive science.

Production Runtimes

Our agents run on durable, event-driven infrastructure that handles timeouts, retries, and network partitions gracefully.

Ready to delegate?

Identify a high-friction workflow. We'll build a proof-of-concept agent in 2 weeks that automates it end-to-end.

Scope Your Agent