Services
AI Delivery
Hands-on delivery of voice, conversational, and agentic AI, through a vetted, technology-neutral partner bench.
At a glance
- Who it's for
- Firms with a use case or roadmap already defined, needing engineering capacity to build it, or to extend their own team.
- Typical sponsor
- CIO, CTO, VP Engineering, or the use case owner.
- Format
- Fixed-scope delivery, or staff augmentation, agreed in writing.
- You end with
- A working system in production, or an embedded team shipping against your backlog.
Why it matters
Most firms that finish Use Case Discovery or stand up a CoE still need hands to build. Sourcing and vetting delivery firms alone takes time most teams do not have. AI Delivery gives you one accountable point of contact, a technology-neutral build matched to your stack, and the same three-check validation standard used across our other services.
Signs you need this
- A use case or roadmap is defined, but you lack the engineering capacity to build it.
- You need voice, conversational, or agentic AI built, not only advised on.
- You want one accountable vendor, not several subcontractors to manage directly.
What you get
- Sourced and vetted delivery team: Engineers matched to the skill the use case needs: voice, conversational AI, or agentic systems.
- One accountable point of contact: Abhishek stays accountable for the engagement, whatever the partner mix behind it.
- Technology-neutral build: AWS, Azure, Microsoft Foundry, or Google, matched to your existing landscape.
- The same validation standard: Grounded to an approved source, a golden evaluation set, and model-as-judge review before anything ships.
- A format that fits: Outcome-owned delivery against a fixed scope, or staff augmentation against your backlog.
- Handover that sticks: Documentation and knowledge transfer so your team can run what was built.
Example format. Not client data.
Sample delivery kickoff checklist
- Use case and acceptance criteria confirmed
- Format agreed: outcome-owned or staff augmentation
- Technology stack and environment access confirmed
- Partner team matched and onboarded
- Validation standard and release gate agreed
How it runs
- 01ScopeConfirm the use case, acceptance criteria, and format: outcome-owned or staff augmentation.
- 02SourceMatch the engagement to the right partner bench for the skill and stack required.
- 03BuildDeliver against the agreed scope or backlog, under the three-check validation standard.
- 04Hand overDocument the system and transfer ownership to your team.
What we need from you
- A defined use case or backlog to work from.
- A named internal owner for the engagement.
- Access to the relevant systems, data, and environments.
- Decision rights agreed up front for outcome-owned delivery.
The method behind it
Every release is held to the three-check standard: grounded to an approved source, passing a golden evaluation set, and cleared by an independent model-as-judge review, regardless of which partner built it.
Illustrative scenarios
Illustrative scenario. Not a client case study.
Insurer with a roadmap but no engineering bench
Use Case Discovery produced a ranked roadmap, but the client has no internal team to build conversational AI.
Approach: Ramanova as the named vendor, sourcing conversational AI engineers from a vetted partner, delivering the first use case to production under the three-check standard.
Illustrative scenario. Not a client case study.
Asset manager scaling an internal agentic AI team
An internal team is building agentic AI but lacks specialized engineering depth.
Approach: Staff augmentation: engineers embedded under the client's direction, with the client retaining ownership of the outcome.
Related
Questions on this service
All questions- Comes after a roadmap is set: Use Case Discovery
- Often paired with ongoing oversight: Advisory Retainer
- A 15-minute call
- A scoping session
- A fixed-scope proposal