Production agent workflows
Multi-agent systems integrated with your systems of record — ticketing, ERP, core banking, case management — doing measurable work.
Services · 02
Agents built like the production software they are.
Triage queues, document pipelines, reconciliation, correspondence — agentic systems now do real operational work. We engineer them with the discipline that work deserves: evaluation suites, permissions, audit trails, rollback plans.
The situation
The demo is easy now. Any team can wire a model to a few tools and watch it book a meeting. The distance between that demo and a system your compliance team will sign — one that touches customer records, moves money, or answers citizens — is measured in evaluation coverage, permission design, and observability. That distance is where we work.
Our agentic builds start from the failure modes: what happens when the model is wrong, when the tool times out, when two agents disagree, when an auditor asks why. Every action is logged, attributable, and reversible. Every capability is gated to a risk tier you approved. The result is automation your risk function defends, not tolerates.
What we deliver
Evaluation harnesses
Task-level success metrics run on every change, so regressions are caught in CI — not by your customers.
Guardrail architecture
Permission boundaries, human checkpoints, and escalation paths matched to the risk tier of each action.
Full observability
Every agent decision traced, logged, and replayable — audit-ready by construction.
Runbooks & failure drills
Operational playbooks for degradation, rollback, and incident response, rehearsed with your team before go-live.
How the engagement runs
Weeks 1–2
Scope the work
Pick one workflow with a clear baseline: volume, cost, error rate. Define what the agent may and may not do, and who signs off.
Weeks 3–8
Build against evals
Iterate on real cases with the evaluation harness as the gate. Your operators review outputs weekly; thresholds are agreed, not assumed.
Weeks 9–12
Harden & hand over
Load testing, red-teaming, failure drills, and progressive rollout — shadow mode, assisted mode, autonomous within tier.
How success is measured
- Task success rate vs. agreed baseline, measured continuously
- Zero unaudited actions — every step traced and attributable
- Human review load trending down as eval confidence rises
- Cost per case and cycle time vs. the pre-agent baseline
Straight answers
We’re vendor-neutral and eval-driven: the stack is chosen against your data residency, cost, and Arabic-performance requirements — and we show the benchmark results that justified the choice.
Then we build assisted-mode systems with human sign-off — and instrument them so the case for expanding autonomy is made with your own data.
Ours do. Arabic task performance is part of the evaluation suite from day one, including dialect handling where the workflow demands it.
Scope a agentic systems engagement.
One paragraph on where you are, and we’ll come back with the shape of the engagement we’d run — scope, duration, and the number it should move.