23 · Access International productDelivered at our clients

Agentic workflows — Multi-agent AI orchestration in production

Run multiple specialized AI agents together, on real business task chains — without breakage and without rogue agents.

Design and operation of agentic workflow chains: several specialized AI agents (research, writing, validation, publishing) coordinated around explicit orchestration (n8n, Airflow, custom). The promise is not multi-agent magic: it is the discipline of a chain that runs in production every day, with human checkpoints, decision logging, source allowlists, and inference-cost governance. Validated in production on a real Middle-East economic think-tank case since late 2025.

Goal
Have several specialized AI agents collaborate on a business task chain, without any of them going off-script.
How
Multi-agent orchestration platform + selective supervision + full journaling + guardrails.

Benefits

  • Proven production discipline: 5 live workflows run daily at a think-tank client — not a lab POC
  • No rogue agent: human checkpoints on risky steps, source allowlists, complete and auditable decision logging
  • Native FinOps governance: per-agent and per-run inference costs traced, premium vs. low-cost LLM arbitrated by criticality
  • Combinable with HITL framework and RAG documentation for critical chains (banking, public sector, regulatory compliance)
Access reference — already deployed in production
Sector
Economic think tank · MENA
Delivery mode
Development cell + continuous run
Volume / scope
5 agentic workflows live in production (research, writing, newsletter, tenders, publishing), 143+ auto-generated articles published on public portal
Stack
n8n · Claude · OpenAI GPT-4o · WordPress · Gamma · Google Workspace
Status
Live since late 2025, continuous iterations, KPIs defined (5-7 articles/week, relevance score > 6/10)

Reference anonymized under confidentiality. Details available on request under NDA.

Customer experience impact

Governed AI industrialization, not a tradeshow demo

An actor moving from isolated AI experiments to an agentic chain running in production every day, with FinOps governance and decision auditability, changes scale and credibility. The doctrine is clear: we do not deliver a meeting-room demo, we deliver a system that runs and that you can maintain. Expected impact: industrialization of high-volume editorial and operational tasks, time freed for teams on value-adding decisions, predictable AI budget framing.

Typical use cases

B2B editorial chains (think tanks, media, sector observatories), marketing automation (newsletters, social posts, slides), structured competitive intelligence, RFP / tender processing, multi-channel operational support.

Editorial chain for think tank and B2B media

Live client case (Middle-East economic think tank): 5 coordinated workflows automatically produce sector intelligence, write sourced long-form articles, publish on WordPress portal, generate Gamma presentation slides. Pipeline: research agent (allowlisted sources) → writing agent (Claude long-form) → factual-validation agent (optional human checkpoint depending on score) → publishing agent (WordPress) → slides agent (Gamma). 143+ articles published to date.

Structured competitive intelligence

Recurring workflow (daily or weekly) that scans allowlisted sector sources, extracts competitor signals, classifies by topic, produces a structured brief for sales teams. Standardized output (Notion, Slack, email per preference) with clickable source links and declared confidence level.

RFP and tender processing

Pipeline that ingests an incoming RFP (PDF, email), extracts structured requirements, cross-references a base of standard responses and Access realizations, produces a draft response prioritized on highest-value sections, flags requirements without documented response. Mandatory human validation before sending — AI accelerates, humans decide.

Multi-channel marketing automation

Chain that turns a product brief or event into multi-channel content: long-form site article, executive LinkedIn post, Facebook/Instagram post, sales Gamma slides, Brevo mailing. Editorial coherence ensured by a supervisor agent that validates message coordination before multi-channel publishing.

Business functions served

Business functions served

This product applies to the following business functions. Click to discover how we adapt it to each.

Frequently asked questions

Frequently asked questions

Multi-agent = chaos. How do you avoid rogue agents?+

Three disciplines. Explicit orchestration (no opaque AutoGPT-style auto-orchestration): every step declared in n8n, every transition documented, every LLM call traced. Human checkpoints on risky steps: final publish, spend > threshold, source allowlist exit. Source and tool allowlist: an agent can only query sources and call tools explicitly declared in its scope. If you want "an agent that does everything alone", we are not the right partner.

Which LLMs do you use?+

Mixed by step criticality. Claude (Anthropic) for long-form writing, complex reasoning, factual validation (observed superior quality on these tasks in our workflows). OpenAI GPT-4o for multi-modal tasks (image, table structure) and steps where speed matters more than depth. Open-source models via Groq for low-criticality steps (simple classification, field extraction) to optimize costs. The LLM choice per step is explicit and arbitrated at scoping.

How much does an agentic chain cost in inference?+

It varies with volume and complexity. On the think-tank case, monthly inference cost remains below 200 EUR for 5 workflows running daily and producing 143+ long-form articles over the period. Levers: premium vs. low-cost LLM arbitration by criticality, request batching, response caching on stable sources. A FinOps dashboard ships with the chain for monitoring and alerts.

Can you plug the chain into our internal systems (CRM, ERP, DAM)?+

Yes — that is even the most frequent target use case. n8n has native connectors for most CRMs (HubSpot, Salesforce, Pipedrive, Microsoft Dynamics), ERPs (SAP, Odoo, Oracle), DAM, ESP, and collaboration tools (Slack, Teams, Notion). For proprietary systems without a native connector, we write a custom connector or expose a thin API layer. Access and secret governance is framed at Intake.

Time to put an agentic chain into production?+

4 to 12 weeks depending on complexity. For a typical editorial chain with 3-5 workflows and standard connectors (CMS, mailing, slides), plan 4 to 6 weeks: 2 weeks of scoping and design, 2-3 weeks of development and tests, 1 week of hyper-care. For complex chains integrating internal systems and multiple HITL, 8 to 12 weeks.

Want to explore this product in your context?

Free initial scoping, 30 minutes to 2 hours, with a solution lead adapted to your sector.