Work - Representative engagements

Anonymized examples of agent systems shipped into real operations: orchestration, guardrails, integrations, and measurable outcomes.

What we deliver - Agent systems you can operate

We design and build production-grade agent systems: scoped autonomy, measurable quality, and safe integration into existing workflows.
  • Strategy to architecture. Define outcomes and constraints, then translate them into a system design you can ship.
  • Workflow automation. Orchestrate long-running, multi-step work across tools and teams with clear handoffs.
  • Production hardening. Add guardrails, approvals, observability, and evals so reliability improves over time.
  • Grounded intelligence. Retrieval, data boundaries, and access patterns that keep outputs tied to reality.
  • Reliability & operations. Monitoring, incident workflows, and safe-action playbooks for real systems.
  • Security-by-design. Least-privilege actions, audit trails, and human-in-the-loop control as defaults.

Engagement - From prototype to production

We move quickly, but we don’t skip the work that makes systems reliable: integrations, safety rails, and operational readiness.
  • Discover. Identify the highest-leverage workflow, define success criteria, and map data and system boundaries.
  • Build. Ship a thin slice on real workflows, then add guardrails, evals, and observability to harden behavior.
  • Operate. Roll out safely with runbooks, monitoring, and iteration loops that make the system measurably better over time.

Work - Representative engagements

Each write-up is anonymized. We focus on the system: architecture, integrations, safety rails, and operational outcomes.

Engagement 01

Revenue operations team

Workflow automation, Agent orchestration, Integrations

Workflow agents for faster revenue operations

A network of AI workflow agents that qualifies leads, drafts compliant outreach, and manages long-running follow-ups across systems.

Teams were spending too much time on repetitive tasks while high-quality leads were missed or handled late.

We implemented collaborating agents to qualify, draft, route, and hand off work to humans at the right moment with full state tracking.

Read case study

Engagement 02

Large-scale platform team

Reliability engineering, Agent systems, Observability

Reliability agents for incident response and uptime

Autonomous reliability agents that monitor systems, detect degradation, recommend safe actions, and produce post-incident learning with guardrails.

Complex distributed systems created alert fatigue and slower incident response times.

We built reliability agents that correlate signals, assist root-cause analysis, and support safer recovery actions.

Read case study

Engagement 03

Operations team

Agent systems, Decision intelligence, Observability

AI agents for operational decision intelligence

A multi-agent system that turns noisy operational data into explainable, action-ready recommendations with human oversight.

Operational teams were drowning in dashboards, logs, and alerts, but still making decisions late and manually.

We shipped an agent system that detects signals, enriches context, and recommends next-best actions with clear audit trails.

Read case study

What teams say - Outcomes over output

Proof shows up in reliability, speed, and the ability to operate what you ship.
“Exceptionally strong ownership. They coordinated integrations, rollout, and operational readiness end-to-end.”

Senior Program Manager

Product engineering team

“We got to production without rewriting everything later. Clear guardrails, measurable quality, and clean handoffs.”

Engineering Lead

Enterprise platform team

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  • Bangalore
    9th floor, BLOCK D3, Manyata Tech Park Rd, Manayata Tech Park, Thanisandra, Bengaluru, Karnataka 560045