AI Agent Development
We build domain‑specific AI agents that reason, retrieve, and take safe actions to automate real work from operations and support to analytics and ecommerce.
- / Trust By
Built with LangGraph, ReAct, Python, FastAPI. Tool use, memory/RAG, safety guardrails, and evaluation are built‑in so agents improve over time.
Policy‑aligned
Tool‑using
Production‑ready
- / Techstack
Built with modern, proven AI technologies
Agent types
Start focused for week‑one value; expand into multi‑agent systems as ROI becomes clear.
Ops Agent
Triage tickets, execute SOPs, update systems, and orchestrate approvals.
Support Agent
Retrieve answers with citations, draft replies, escalate with full context.
Ecommerce Agent
PDP Q&A, guided discovery, returns, order updates, and CRM sync.
Analytics Researcher
Query data via SQL tools, generate narratives and charts with citations.
DevOps Helper
Incident summaries, safe command proposals, PR checklists, runbooks.
Finance Ops Agent
Invoice matching, anomaly flags, compliance checks, and workflows.
Core capabilities
Everything an agent needs to deliver useful outcomes on day one — and become measurably better by week four.
Tool Use & Actions
APIs, databases, ERPs with allow-lists, schemas, and audit trails.
RAG & Knowledge
Embeddings, citations, freshness policies, and multi-hop retrieval.
Memory & Profiles
Session + long-term memory within privacy and retention rules.
Workflow Orchestration
Graph flows (LangGraph), branching policies, human-in-the-loop.
Safety & Policy Controls
Jailbreak defenses, PII masking, RBAC, rate limits, and approvals.
Observability & Evals
Logging, tracing, red-teaming, and continuous evaluation.
Our delivery process
- / Process
1/6
Use cases, KPIs, risks, and compliance needs.
Define
2/6
Agent graph, memory strategy, policies, UX, and API contracts.
Design
3/6
RAG, tool use, adapters, and automated tests.
Develop
4/6
Security, evals, monitoring, and performance tuning.
Harden
5/6
Canary + A/B, stakeholder training, change playbooks.
Launch
6/6
Feedback loops, tuning, and roadmap expansion.
Improve
- / FAQs
Frequently Asked Questions
- How do you keep agents reliable?
Eval datasets + traces, strict tool allow-lists, retry/critic loops, and human-in-the-loop for risky actions.
- Do you support on-prem or VPC?
Yes. We deploy to Vercel, AWS, GCP, or your VPC with private networking and secrets management.
- Which models do you use?
We are model-agnostic (OpenAI, Anthropic, Gemini, Grok) based on latency, price, and task quality.
- How fast can we launch?
A focused MVP can ship in 4–6 weeks depending on data and integrations.
Ready to ship your agent?
Let’s define the MVP and deploy to your channels with safety, analytics, and measurable impact.