From your first workflow to your hundredth.
Whether you're scoping a single agent or scaling a fleet across the business, we cover the full journey, from strategy through day-to-day operations. Every engagement ends with software in production, not slides.
How we work
We're an AI engineering team, not a product packager. Every engagement starts with your workflows and ends with working software in production. Agents that read the message, take the action, log the result, and pause for a human when judgment is needed. Tailored to your industry, your stack, and how your team actually works.
Service Lines
Four engagements. One agent lifecycle.
Engage us at any stage. Most clients start with Strategy or Build and stay for Operations.
01 · Strategy
Strategy & Roadmap
We map your existing workflows, find where agents return the most value, and produce a sequenced plan from your first deployment through a fleet running across the business. Not a binder. A build plan with effort estimates and clear stop-rules.
- Workflow audit across customer, employee, and back-office touchpoints
- Inventory of the systems an agent could read from and act on, and what's missing
- Ranked list of opportunities by value, risk, and readiness
- Compliance footprint: HIPAA, FERPA, GDPR, SOC 2, data residency where it matters
- 12-month roadmap from your first agent to a fleet
What you get
A ranked agent backlog, a reference design tailored to your stack, a scope for the highest-value first agent, and a clear go/no-go framework for everything that comes after.
Timeline: 3 to 6 weeks
For: Leaders putting real budget behind agents in the next 12 months.
02 · Build
Design & Build
The core engagement. We build the agent end-to-end: what it knows, what it can do, what it remembers, what it escalates. Each part is a real, inspectable artifact your team can read, review, and own.
- Pick the right AI model for the job, and switch as better ones arrive, without rebuilding
- Capture your business policies in plain language. One sentence per rule, version-controlled and testable
- Connect your knowledge (product docs, contracts, customer history, policies) so the agent answers from your truth, not invented facts
- Build the actions the agent can take across your stack, one capability at a time, each permissioned and audited
- Specialist agents for complex flows (one for quotes, one for escalation) that compose like building blocks
- Memory at the right scope: this conversation, this customer, your whole organization
- A continuous quality system so the agent improves, not regresses, with every change
What you get
A production-grade agent reaching Stage 2 to 4 on the capability ladder. Deployed inside your environment, with quality scores, audit logs, and an admin console your team can run on its own.
Timeline: 8 to 16 weeks to production
For: Teams ready to commit a workflow and the data behind it.
03 · Integrate
Enterprise Integration
An agent is only as useful as the systems it can reach. We connect yours to the platforms that actually run your business: CRM, ERP, content, learning, ticketing, communication. With pre-built connectors where they exist and custom ones where they don't.
- Sales & CRM: Salesforce, HubSpot, Microsoft Dynamics
- Operations & ERP: NetSuite, SAP, Workday, Oracle
- Service & ticketing: ServiceNow, Zendesk, Freshdesk, Jira
- Publishing: Klopotek, Biblio, Firebrand, Arc XP, WordPress VIP
- Education: Canvas, Blackboard, Moodle, Google Classroom, PowerSchool, Workday Student
- Healthcare: Epic, Cerner, Athenahealth via HL7 / FHIR
- Communication: Slack, Microsoft Teams, email, SMS
- Anything custom: a clean adapter to your internal services in days, not months
What you get
Every system the agent needs, connected with permissions, rate limits, audit logs, and graceful fallback when something downstream is unavailable.
Timeline: 2 to 8 weeks per integration, runs in parallel with Build
For: Any serious agent. This is where compounding value lives.
04 · Operate
Operations & Evolution
Launch is the start. We run on-call for your agent, watch how it's actually performing, retire what isn't earning its keep, and move it up the capability ladder on a steady cadence. This is where most AI projects quietly stall. We keep ours improving for years.
- Constant monitoring: what's working, what's failing, what needs attention
- Quality testing on every change so the agent never regresses
- Usage and cost dashboards by team, customer, and workflow
- Policy refinement based on actual customer conversations, not guesses
- Quarterly reviews where we plan and ship the next stage of capability
- Move to better AI models as they're released, no rebuild needed
What you get
A monthly operations report, a quarterly capability plan, and an agent that's still earning its keep a year after launch. At Stage 3, then 4, then 5.
Timeline: Ongoing, typically a retainer
For: Anyone who wants their agent to still be valuable in 2027.
Cross-cutting · Trust & Guardrails
Built in from day one. Not bolted on.
Production agents fail in public. We ship every engagement with a trust layer that matches enterprise reality: identity, permissions, approval gates, audit, sensitive-data handling, compliance.
- Strict data isolation between teams, customers, and data types
- Human approval gates for the things that matter: pricing, escalations, regulated communications, sensitive cases
- Every decision logged and reviewable, with the agent's reasoning attached
- Sensitive data redacted before anything leaves your environment
- Compliance presets: FERPA-aware, HIPAA-aligned, GDPR, SOC 2
- Hosting options: managed by us, your cloud (Azure / AWS / GCP), or fully on-prem
For data-sensitive workloads where your information cannot leave your environment (PHI, FERPA records, IP, contracts), see our dedicated Private AI & Security page for deployment options including open-source models in your VPC, frontier models via Bedrock / Azure OpenAI / Vertex, and air-gapped configurations.
The honest answer
Agent + people, not agent vs. people. The agent reads the situation and picks the right action; established systems still execute the deterministic work; humans approve the moments that genuinely need approval. Everything below the agent stays as reliable as it is today.
Our Process
How a Quantilus engagement runs.
Opinionated sequencing. Short cycles. Working software at every checkpoint.
Discover
Map the workflow, the systems involved, the trust requirements, and the stop-rules. Pick the highest-value first agent.
Design
Lay out the whole agent: what it does, what it knows, what it remembers, where humans approve. Aligned with your security and data teams from day one.
Build
Weekly demos against a real quality bar. Capabilities land one at a time. No big-bang launch. Always a working agent.
Operate
Launch behind feature flags, observe real behavior, climb the capability ladder. The agent gets smarter every quarter.