Frequently asked questions

Prestanda is an AI-first enterprise technology consultancy. We advise on, design, build and operate the applied AI, Salesforce, cloud, data and custom software systems that enterprises run on.

The work spans six practices: AI & machine learning; Salesforce; backend, API and integration; cloud and platform engineering; data and analytics; and content platforms and digital experience. Most engagements draw on more than one of them.

We are headquartered in India and serve clients globally, with a significant concentration of work in the United States.

Enterprise and mid-market organisations, largely in the United States. Clients include AT&T, Porch Group, Porch Moving Group, Homeowners of America, Inspection Support Network and Hire A Helper.

Two, both independently appraised: CMMI Level 3 for process maturity and ISO/IEC 27001:2022 for information security management.

Together they cover the two questions enterprise procurement usually asks first — is delivery repeatable, and is our data safe.

Our current partner and alliance set includes Anthropic, AWS, Adobe, Microsoft, IBM, Salesforce, Boomi and E2E Cloud.

With a conversation about the problem, not a proposal. Our delivery process runs in four stages — Discover, Design, Build, then Run & refine.

Discover turns your goals, users and constraints into a plan. Design shapes architecture and experience together, prototyped before production code is written. Build runs in short iterations with working software each sprint. Launch is the midpoint, not the finish line.

CMMI Level 3 means delivery processes are defined, measured and applied consistently across every engagement rather than improvised per project, and that this has been verified by an external appraisal.

In practice it is what makes progress predictable. You see steady output and working software instead of a quiet stretch followed by a surprise. It is a level of process maturity most boutique firms do not carry.

Yes. The senior people who scope an engagement stay on it through delivery. We do not switch to a bench team after kickoff.

We work with an overlap window rather than a full handoff, so client-facing coordination, approvals and escalation happen inside shared working hours while development continues outside them.

Forward deployed engineers sit close to the business problem instead of behind a requirements document — working alongside your teams, seeing the real workflow, and building against it directly.

It suits problems that are hard to specify up front, where the fastest route to something useful is an engineer in the room rather than another round of written specification.

We will tell you. We shape the solution to the business rather than the other way round, and if a commercial product fits better than a custom build, saying so is more useful to you than the engagement would be.

Four broad categories. Predictive AI — models that forecast demand, score risk and support decisions. Generative AI — enterprise copilots, agents, RAG and document Q&A. Vision AI — turning photos, documents and field evidence into auditable decisions. Physical AI — robotics, simulation and sensor-aware operational workflows.

The common thread is production. We build AI that is evaluated, monitored and integrated into a real workflow, not demonstrated in a slide deck.

Auralis is our sovereign AI platform. It runs private AI agents, grounded question answering and local language models entirely on infrastructure you own — your data does not leave your building, and every answer cites the source it came from.

Yes. This is what Auralis is for. Retrieval, analysis and model inference all run locally, with nothing sent to an external AI provider.

It matters for organisations with data residency rules, regulated data, or a policy against sending internal material to third-party models.

By making evidence a requirement rather than a preference. Answers are generated only from retrieved source material, every material claim carries a citation back to the record it came from, and when the evidence is not there the system says so explicitly instead of filling the gap from general knowledge.

Abstention is a feature. A system that admits it does not know is the only kind you can safely build a business process on.

We separate activity from deliverable from outcome from business value, and report every claim at the highest rung its evidence supports — never higher.

Alongside that runs an evidence maturity scale, from value that has been observed and confirmed down to an explicit “insufficient evidence” level. Without that discipline, AI reporting becomes an inflation machine: language models are very good at making effort sound like achievement. We wrote up the full framework in Measuring the business value of AI agents.

Implementation, integration, customisation, migration and ongoing support — through to training your own team. The goal is a Salesforce estate your people can actually run.

Yes, and it is often the harder half of the work. Our backend, API and integration practice builds the connective tissue between Salesforce and the systems around it — application backends, APIs, webhooks and platform integrations engineered to stay reliable at scale.

Our information security management system is certified to ISO/IEC 27001:2022, which means controls are documented, audited and reviewed rather than assumed.

Where data sensitivity rules out third-party AI services entirely, Auralis lets the whole AI stack run inside your own infrastructure.

Our own handling of personal data is governed by India's Digital Personal Data Protection Act 2023 and the EU GDPR. The detail is in our privacy and cookie policy.

Email sales@pcplusa.com, call +91 88001 99207, or use the form on our contact page.

Nothing formal. The problem you are trying to solve, who it affects and what you have tried already is enough to make the first call useful. Requirements documents can come later — often they come out of Discover rather than into it.