AI-native operating consultancy
We install the AI operating model. Then we build the software it needs.
Most enterprises do not have an AI problem. They have three pilots, no owner, and no pass line. We fix the operating model first, then build the applications that carry the work.
Chennai and remote · India and the United States · fixed fee, fixed duration
What we are not
- Not a staffing firm. We do not sell seats and we do not compete on hourly rate.
- Not a platform reseller. We have no licence revenue riding on your architecture choice.
- Not an innovation theatre supplier. A prototype with no named decision attached is work we decline.
- Not a large team. Senior people, small engagements, and a stated refusal list.
The problem
Pilots do not fail on model quality. They fail at the seam.
Three patterns account for most stalled enterprise AI work, and none of them is technical.
01
No owner
The metric belongs to a committee. Committees do not defend numbers in a review; named executives do.
02
No workflow change
AI applied to an unchanged process makes one step faster while the queue in front of it stays exactly where it was.
03
No pass line
Success criteria written after results arrive cannot be failed, which means they cannot be met either.
The NATIVE framework
Six stages, published in full and free to use
NATIVE is our advisory spine. It is not gated, because a framework you cannot inspect is a sales asset rather than a method.
- NNotice
What the market is already telling you
What is changing around us that we cannot afford to ignore?
- AAssess
Are you ready, really?
What can this organisation actually absorb now?
- TTarget
Choosing the battlefield
Where does AI connect to a business outcome worth owning?
- IIntegrate
Rewriting workflows and decision rights
How does the work itself need to change?
- VValidate
Prove it before you scale it
Did it produce value, quality, adoption, and acceptable risk under real conditions?
- EExpand
When the pilot becomes reality
How do we make the gain durable without breaking the system around it?
Two pillars, one practice
Advice that has to survive delivery
We advise and we build. That means our recommendations carry consequences we have to live with.
Pillar one
AI consulting
Readiness diagnostics, strategy and roadmap, operating model design, governance, model risk, and fractional Chief AI Officer engagements.
Explore the advisory pillar
Pillar two
AI software development
Custom AI applications, agents, enterprise RAG, LLM engineering, legacy integration, and the twelve-gate path from proof of concept to production.
Explore the build pillar
AI Strategy and Operating Model
AI Readiness Diagnostic
A scored assessment across leadership commitment, data usability, workflow clarity, and governance, with a named owner assigned to the weakest pillar
AI Strategy and Operating Model
AI Strategy and Roadmap
A sequenced twelve-month plan built from a triaged use-case shortlist, each item carrying a metric, an owner, and a validation method
AI Strategy and Operating Model
Use Case Portfolio Design
Reduce a long list to a defensible shortlist using three gates: strategic consequence, measurability, feasibility
AI Strategy and Operating Model
AI Operating Model Design
Decision rights, governance cadence, funding model, and the choice between a central centre of excellence, federated pods, or both
AI Strategy and Operating Model
Fractional Chief AI Officer
Senior AI leadership on a defined monthly commitment, owning the loop rather than advising on it
AI Strategy and Operating Model
Board and Executive Briefings
Half-day and full-day sessions for boards and leadership teams, built on the NATIVE framework and the RAO prompt standard
Proof, Product, Platform
A ladder you can stop climbing at any rung
Each stage ends in a decision. A decision not to proceed is a completed engagement, not a failure.
Pre-Proof
The NATIVE Audit
15 minutes, self-serve
Free. No discovery tax, no call required.
- An interactive scored assessment across the four readiness pillars
- A one-page summary you can circulate
- The weakest-pillar diagnosis with the question to take into your next leadership meeting
Pre-Proof
AI Readiness Diagnostic
3 to 4 weeks
Fixed fee. Comparable enterprise AI assessments from large consultancies are commonly quoted in the $50,000 to $150,000 range.
- Pilot and shadow-AI inventory
- Two named structural market signals
- Four-pillar readiness score with named owners
Proof
Prototype Sprint
2 to 3 weeks
Fixed fee, published.
- A working prototype on your workflow
- A before-and-after workflow map
- A build-or-stop recommendation with a named decision owner
Product
First Workflow Build
6 to 12 weeks
From a published figure. Three variables move it: integrated systems, regulatory review, and whether an eval harness is required.
- One production application
- An integrated redesigned workflow with named approve, override, and escalate roles
- A pilot charter with a pre-written pass line and kill switch
The ninety-day scorecard
What you should be able to show, and what a weak answer sounds like
Send this to whoever prepares your board pack. It is deliberately uncomfortable.
Day 30, audit
An inventory of every active pilot and shadow tool, two structural signals in one sentence each, and a four-pillar score with a named owner on the lowest pillar.
"We are exploring several initiatives across the business and building excitement."
Day 60, design
A shortlist of one or two use cases that survived three gates, a completed value map with a written baseline, and Approve, Override, and Escalate named for the specific workflow.
"We have identified a number of high-impact opportunities and are socialising them with stakeholders."
Day 90, execution
A signed pilot charter, results against a pre-written pass line, a fully loaded cost comparison, and a decision: expand, stop, or narrow.
"Early feedback has been very positive and the team is keen to keep going."
Evidence
Use cases, not client logos
Our clients do not want their AI programmes described publicly, so we publish the workflow, the measurement basis, and what did not work.
Manufacturing · Finance
Reducing month-end reconciliation review time in a mid-market manufacturer
Review time per close cycle fell from 38 hours to 11 hours
9 weeks
Banking and financial services · Credit risk
Compressing credit file preparation in a commercial lending team
Preparation time per file fell from 6.5 hours to 2.75 hours, at equal committee rework rate
11 weeks
GCC in India · Shared services and IT
Clearing a three-quarter internal tool backlog in a GCC
Nine tools published in one quarter against a prior run rate of two, with median request age falling from 9 months to 6 weeks
One quarter, first wave
Industries
Where the constraints differ, the sequence differs
Insights
Written for people who have to decide
The NATIVE series · 7 min read
Why AI pilots fail at the seam, not at the model
Three failure patterns account for most stalled enterprise AI pilots, and none of them is model quality.
AI economics · 8 min read
The fully loaded cost of an AI workflow
Most AI business cases exclude the largest variable cost in the workflow: the human review the design requires.
Governance and risk · 6 min read
What a weak AI board update sounds like
Boards rarely lack AI updates. They lack updates with a number, an owner, and a date in them.
Governance and risk · 6 min read
Shadow AI is a speed problem, not a discipline problem
Prohibition moves the risk out of view. An inventory and a faster sanctioned route move it back inside the boundary.
FAQ
Common questions before a first call
- What does Superposition Technologies do?
- We are an AI consulting and AI software development firm. We install a governed AI operating model using the NATIVE framework, then build the applications that operating model needs. Advisory and build are one practice, not two vendors.
- Where are you based and who do you work with?
- We are headquartered in Chennai, India, and work with enterprises across India and the United States, typically between $50M and $1B in revenue, or the Indian equivalent.
- How do you price work?
- Fixed fee, fixed duration, named deliverables. No hourly billing and no change order for a question. Bands are published on the pricing page so you can compare shapes before you compare firms.
- What makes this different from a pilot programme?
- A pilot proves a model can work. An operating model decides who owns the metric, who may override the system, what stops the work, and how the evidence reaches a board. We start with the second, because that is where pilots die.
Disclosure
Superposition Technologies participates in the Lovable Solution Partner Program. We describe that relationship as participation in the programme, and we make no claim of certification or partner tier.
Next step
Start with a baseline, not a proposal
Take the NATIVE Audit in fifteen minutes, or book a scoping call and bring the pilots you already have running.