Prepared for Cigna / Evernorth
Stand up the delivery factory.
Then run real software through it.
A 14 week discovery and lighthouse engagement for the greenfield PBM adjudication platform: architecture and charter alignment, foundational pipeline and infrastructure automation, and one real service module onboarded to prove the factory works.
What we heard
Cut the cost to operate the PBM with a greenfield platform on a real competitive clock
The PBM platform runs on COBOL and takes roughly 1,600 people to operate. It is expensive to maintain and slow to change, whether the change comes from regulators or from customers. The mandate is a modern replacement that costs materially less to run, so pricing stays competitive through 2028 and beyond.
The play
Acqui-hire as accelerator
The architecture
Three buckets
The clock
July 1, 2028
The mandate
First 90 days = delivery factory
The AI posture
Build on what Cigna already proved
The end state
Capability inside your four walls
Our proposal
Three equal legs: modernization and architecture, delivery foundations, and enablement
The engagement chunks into three visible buckets that run concurrently over 14 weeks. Application architecture and modernization is a core pillar, not an adjacency: we lead the architecture discussions, run proof-point experiments to determine what good looks like across application architecture patterns, and set the best practices the platform is built on. Discovery does not gate delivery; the lighthouse module validates the factory while the factory is being built.
Bucket A
Modernization
Application architecture patterns, decomposition, proof-point experiments
Bucket B
SDLC
Golden-path pipelines, environments, test data and evidence
Bucket C
Enablement
Paired delivery, agentic SDLC adoption, operating model
Discovery & Application Architecture
- Charter, goals, objectives and success measures with the Cigna leadership team
- Liatrio leads the architecture discussions and defines best practices across application architecture patterns, not only SDLC enablement
- Architecture proof-point experiments: small, time-boxed builds that establish what good looks like before patterns are locked in
- Current-state assessment of the acquired platform: services, data, Oracle/PL-SQL footprint, Azure VM estate
- Future-state cloud-native target architecture and decomposition strategy, with honest, evidence-based recommendations even where they challenge prior M&A disposition decisions
- Migration and coexistence view against the 2028 date and the 2–3 year onboarding window
Required talent from Cigna
At minimum one product owner for the delivery platform, and one for the new version of Express Scripts. Plus named architecture counterparts from Cigna and the EA team.
Delivery Foundations (the factory)
- Golden-path CI/CD pipelines with policy, security and compliance evidence built in
- Infrastructure automation as code across the new AWS/Azure subscriptions
- Environment strategy, test data strategy, and end-to-end testing patterns
- Observability, cost and FinOps guardrails from the first deployment
- Agentic SDLC patterns wired into the path to production: spec-driven, reviewable, auditable
Required talent from Cigna
Platform and cloud engineers to pair with us, plus a security/GRC counterpart who can approve guardrails and evidence patterns as they are built.
Lighthouse Module & Modernization (proof point)
- Select one representative use case to prove and harden the delivery foundation
- Stand up the test data strategy this platform needs: synthetic and anonymized data sets given PHI restrictions in the clean-room environment, golden data sets, data migration testing woven into the SDLC, and environment data lifecycle management
- Modernize the module against the target application architecture patterns, proving the decomposition approach on real code
- Build and ship it through the blueprint factory floor, end to end
- Optionally prove it safely against traffic in lower stage environments
- Publish the blueprint so the next 10 modules are a repeat, not a re-invention
- Pair the acquired team through the build so the capability stays with them
Required talent from Cigna
A domain SME for the selected use case, a data/test-data counterpart, and engineers from the acquired team dedicated to pairing through the build.
14 weeks
What lands, and when
Weeks are indicative and will be firmed up in the SOW. Tracks overlap by design.
Weeks 1–3
Align & instrument
Charter and objectives confirmed. Architecture discovery underway. First pipeline skeleton and landing-zone automation in place. Lighthouse module candidates identified with your architects.
Weeks 4–7
Build the factory floor
Golden-path pipeline with security, policy and evidence. Environments and test data strategy live. Target-state architecture draft under review. Lighthouse module design and build starts.
Weeks 8–11
Run software through it
Lighthouse module flowing through the factory to a production-like environment. Agentic SDLC patterns in daily use by the paired team. Integration and end-to-end testing approach validated.
Weeks 12–14
Prove, publish, scale-plan
Lighthouse demonstrated (optionally against shadow/canary traffic). Blueprint and operating model documented. Roadmap, team topology and scale plan for the next phase into 2028.
Team structure
The Liatrio team for the 14 weeks
1
Engagement Lead
Strategic Principal
1
Delivery Lead
Delivery leadership and cadence
1
Technical Lead
Architecture and technical direction
4–6
Sr. App Mod & Platform FDEs
Forward deployed engineers building and pairing
Ad hoc Liatrio support
Field CTO, Technical Associates and Innovation team members pulled in as needed, at no additional cost, for architecture reviews, emerging-tech spikes and thought leadership.
Scaling model
Start lean, then scale the modernization pods as the codebase reveals itself
The 90 day team above is deliberately lean. Once we have access to the acquisition's codebase and the unknowns surface, the growth happens on the modernization and architecture side: additional app mod pods pattern-matched to the decomposition plan, each one paired with Cigna engineers so capability scales with headcount.
Stage 1
Weeks 1–14
Lighthouse team
7–9 Liatrians
1 Engagement Lead, 1 Delivery Lead, 1 Technical Lead, 4–6 Sr. App Mod & Platform FDEs. One lighthouse pod proving the factory and the architecture patterns.
Stage 2
Post-lighthouse
Two to three app mod pods
~14–20 Liatrio
Blueprint replicated. Each pod is 1 Tech Lead plus 4–6 App Mod FDEs against a domain slice, plus a shared platform pod holding the golden paths and test data strategy.
Stage 3
Scaled modernization
Pod-of-pods toward 2028
Scales with domains
Pods added per adjudication domain, increasingly staffed by Cigna engineers as Liatrio steps back. Architecture guild and platform pod remain constant to hold standards.
How we decide to scale
Scaling is triggered by evidence, not by calendar: a proven blueprint, a decomposition plan with sized domain slices, and Cigna engineers ready to pair. We would rather add the fifth pod late than add it before the pattern holds.
Outcomes you keep
What we need from you
Why Liatrio
We are not a staffing firm, and this is not a paper exercise
We roll up our sleeves
From the first weeks we are building: pipelines, infrastructure, and a real module that becomes a valuable proof of concept, designed from day one to scale into the next phase. You will see working software, not a deck about working software.
Your team owns it
Our industry-unique approach empowers your teams to own the capabilities, the operating model, and every aspect of the initiatives we take on together. You will not find another partner offering this; most providers are services-only, and those are plentiful.
We do the technical work and guide the journey
This effort involves hard decisions, change management, AI-native upskilling, complex workflows and deep modernization. We handle the technical work and coach your people through all of it, so the capability compounds inside your four walls instead of walking out the door with a vendor.
Application architecture depth
We lead architecture, define the patterns and modernize real code; CI/CD is table stakes, not the offer.
Enablement over augmentation
Dojo-style capability building, not arms and legs.
Agentic SDLC, done responsibly
Spec-driven, reviewable, cost-instrumented AI delivery.
Regulated-industry fluency
Healthcare, life sciences and payer-grade guardrails, including synthetic and anonymized test data at scale.
Investment
Outcome focused engagement with monthly billing
14 week discovery + lighthouse
$1.1M – $1.4M
An outcome focused engagement with set monthly billing based on affirmed progress toward target outcomes, not time and materials. The range reflects final scope: the number of architecture proof-point experiments, the breadth of the test data strategy, and the size of the lighthouse module. We will narrow this range as we get full alignment from this team, and lock a single figure in the SOW with the boundary conditions, assumptions and scope written down.
Covers the blended Liatrio team across all three buckets: modernization and architecture, delivery foundations, and enablement. Excludes cloud consumption, third-party licensing and AI token spend, which we help you forecast and instrument during the engagement.
Next steps
- 1Incorporated feedback from the session with Steve, Patrick, Will and Tom into this proposal; discuss another session to identify lighthouse candidates.
- 2Liatrio issues the full proposal and SOW, and we move fast, at your startup pace.
- 3Kickoff sourcing process in parallel to pre-engagement discovery and identifying engagement kickoff.
Predictors for success
What makes this engagement move at startup pace
These are the conditions we have seen separate fast programs from slow ones. We will work with you to shape them together as part of scoping.
Freedom to reinvent GRC
Room to define, automate and streamline governance, risk and compliance processes so timelines are optimized rather than queued.
Ownership of cloud infrastructure
Direct ownership of IAM, network, subscriptions and account access inside the walled-off domain.
Budget for agentic tooling
Power-user level agentic coding tools for the combined Liatrio and Cigna team, planned around $4–5k per user per month.
Close product partnership
Product management collaborating closely with delivery teams, ideally with PMs embedded directly on the teams.
Autonomy on tool selection
Ability to choose best-in-breed tools and technologies for the specific use cases that emerge.
Guardrails owned by product teams
With freedom and autonomy comes accountability: automated, visible guardrails that keep AI-assisted delivery safe and high quality.
Proof points
We have done this in regulated, high-stakes environments
Case study: Natera
From fragmented delivery to a governed, self-service platform
Natera, a leader in cell-free DNA testing, needed to scale software delivery in a heavily regulated diagnostics environment without slowing its engineers down. Liatrio partnered with their teams to establish golden-path pipelines, infrastructure automation, and a modern PMO/product operating model, then paired directly with Natera engineers so they owned the platform from the outset. Delivery foundations were proven with real product workloads flowing through them, not a pilot on the side.
Days → minutes
Environment provisioning through automated golden paths
Compliance by default
Policy and audit evidence generated by the pipeline
Owned in-house
Natera teams running and extending the platform themselves
Highlighted client portfolio
