Turn Broken Handoffs Into Production AI Workflows
Agentic Workflows apply Enterprise Context Engineering to a specific operational bottleneck—connecting systems, structuring context, and shipping a working AI workflow your team can use every day.
Discovery → workflow selection → production implementation in 4–6 weeks
Built for teams with repetitive handoffs, inconsistent execution, and measurable operational bottlenecks.
20+ years engineering leadership · 100+ products shipped · production AI systems across Sales, Ops, Support
Why AI workflow projects fail to reach production
Most AI workflow initiatives stall because the surrounding systems, integrations, and feedback loops never get built.
Demo-ware, not production
Your AI POC dazzled in the demo. Three months in, no one uses it. Accuracy drifted, outputs stopped at drafts, no one wired it into the CRM.
Platform-first projects stall
"Build the AI platform first" becomes a 12-month roadmap. Business outcomes are 18 months away. You need a win in six weeks.
No production path
Scripts live in notebooks. Outputs stop at email drafts. Nothing is integrated with Salesforce, Zendesk, Google Workspace — where the work actually happens.
No feedback loop
AI output quality decays. No one is measuring it, let alone improving it. The model gets dumber while everyone assumes it is getting smarter.
From manual handoffs to operational execution
The same business outcome. One has six people copy-pasting between tools. The other runs daily on its own — with a human in the loop where it matters.
Six disconnected tools. Institutional knowledge trapped across people and systems. 20+ hours per week spent stitching work together.
Connected systems in. Structured execution. Human approval where needed. Reliable outputs back into your workflows.
What an Agentic Workflow implementation delivers
A production AI workflow built around a specific business handoff—fully integrated, measurable, and ready for daily use.
- Working AI system producing the output daily (or on-demand)
- Integrated with your source-of-truth systems (CRM, docs, ticketing)
- Feedback loop and evaluation pipeline built in
- Monitoring, alerts, and accuracy dashboards
- Runbooks for the team that owns the workflow
- A foundation that the next 2–3 workflows snap into
Explore workflows we ship.
Each one shipped end-to-end in 4–6 weeks. Pick the shape closest to yours.
Sales briefs
Pre-meeting deal briefs
Pulls the account, recent calls, and open tickets together into a one-page brief delivered to the AE before every customer meeting.
How Agentic Workflows engagements start
A focused implementation path designed to create measurable value quickly.
Discovery call
30 minutes to walk through where AI is stuck, which workflows the business actually values, and which one we would bet on.
A shortlist of workflows ranked by ROI and complexity.
Opportunity map
One-week turnaround: 3–5 workflows prioritized by value, feasibility, and the path to production. Fixed scope for the first build.
A plan you can get leadership behind.
First working system
Senior engineers build and ship the chosen workflow in 4–6 weeks. Production deploy, feedback loop, and handover.
A production AI system delivering measurable outcomes.
What ships
The artifact, not a slide deck.
Every workflow ends in something concrete: a brief, a draft, a score, a routed ticket. Grounded in your data, with provenance and an eval score on every output.
- ✓ Source-grounded — every fact traceable to a system of record.
- ✓ Eval-scored — accuracy and grounding measured before each output ships.
- ✓ Versioned — every run is a reproducible artifact with a diff against the last one.
Brief
Deal Brief — Acme Corp · Renewal Meeting
Account snapshot
SalesforceAcme Corp · $480k ARR · renewal in 27 days · sponsor Mara Chen (CRO, joined 14 months ago).
What changed since last QBR
Gong · ZendeskDaily active seats up 18%. Two P2 tickets opened around the new permissions model — both resolved in <24h. CRO mentioned procurement reshuffle on the last call.
Recommended angle
Agent reasoningLead with usage uplift, address the permissions concern up-front, and pre-stage procurement docs given Mara's note about the reshuffle. Avoid the multi-year discount; her CFO has been resistant.
Every claim links back to its source. Every output runs through an eval before it ships.
Agentic Workflows in practice
See how a fragmented manual process became a production AI workflow delivering measurable operational leverage.
FounderBrand AI — content-automation platform
The problem
Marketing team was manually turning 1-hour founder interviews into 15+ pieces of SEO-optimized content per guest. The process consumed 20+ hours per week and editing fatigue was capping throughput.
The outcome
Shipped an AI pipeline that converts raw video interviews into structured content assets — long-form blog, short-form social, SEO briefs, email drafts. Human editor stays in the loop for voice and quality.
Have a broken workflow slowing your team down?
Let’s assess whether it’s the right fit for an Agentic Workflow implementation.
Built for regulated environments
Your data, your cloud, your controls.
We ship into your environment. Your data never leaves it. Every output is logged, scored, and reversible.
Encryption and isolation by default
- AES-256 at rest, TLS 1.2+ in transit on every hop
- No training on your data. Ever. Contractually enforced with model providers
- Per-tenant keys when you need them; BYOK supported on AWS / GCP / Azure
PII handled, scoped, audited
- PII detection and redaction at ingress, before prompts ever touch a model
- Role-scoped retrieval — agents only see what the calling user is entitled to
- Full audit trail: prompts, retrievals, tool calls, outputs — exportable
Runs in your environment
- Deployed to your VPC (AWS / GCP / Azure) via private endpoints
- Logs stay in your infra; we have no production-data access by default
- SOC 2 Type II and HIPAA-ready stacks available on request
Security review packets, sub-processor lists, and architecture diagrams shared under NDA before any kickoff.
Common questions
Is this an AI platform project?
No—and intentionally so.
Agentic Workflows are focused Enterprise Context Engineering implementations designed to create measurable production value quickly, instead of long platform-first initiatives.
What does it cost?
First workflow runs $100–250k depending on integration complexity and quality thresholds. Discovery call and opportunity map are free.
What workflows do you build?
Deal briefs, proposal drafts, renewal risk scoring, support triage, meeting summaries, report generation, lead enrichment. Anything repetitive, high-volume, and LLM-suited.
Which LLMs and vendors?
We're model-agnostic. Claude, GPT, Gemini, Llama — whatever fits the workflow, your data constraints, and your cost envelope. We evaluate; you own the decision.
What about data security?
Production workflows run on your cloud (AWS/GCP/Azure) via private endpoints. No training on your data. Logs stay in your infra. SOC 2 / HIPAA stacks on request.
How is this different from Zapier or n8n?
Those are great for simple integrations. We build when the logic needs real LLM reasoning, quality thresholds, feedback loops, or handoff to humans — things an automation platform can't maintain alone.
Is this the right fit?
Good fit
- Specific high-value workflow candidate in mind
- One or more AI POCs have stalled at demo or pilot
- Budget for a $100–250k fixed-scope first build
- Leadership alignment on shipping one thing well before scaling
Not a fit
- "We need to build an AI strategy first" — start with AEMI instead
- Looking for a subscription-priced automation platform
- No workflow owner accountable for the outcome
- Budget below ~$80k
Have one workflow you wish was AI-powered?
30 minutes with a CTO to assess the workflow, systems involved, implementation complexity, and likely production path.